Physiological Measurement

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<div class="cf mb-1">    <div class="tabs cf mb-2 mt-1 tabs--vertical" id="wd-jnl-hm-art-list">  <div role="tablist"> <button role="tab" aria-selected="false" aria-controls="most-read-tab" id="most-read" class="event_tabs" tabindex="-1"> Most read </button> <button role="tab" aria-selected="true" aria-controls="latest-articles-tab" id="latest-articles" class="event_tabs"> Latest articles </button> <button role="tab" aria-selected="false" aria-controls="review-articles-tab" id="review-articles" class="event_tabs" tabindex="-1"> Review articles </button> <button role="tab" aria-selected="false" aria-controls="accepted-manuscripts-tab" id="accepted-manuscripts" class="event_tabs" tabindex="-1"> Accepted manuscripts </button> <button role="tab" aria-selected="false" aria-controls="trending-altmetrics-tab" id="trending-altmetrics" class="event_tabs" tabindex="-1"> Trending </button> <button role="tab" aria-selected="false" aria-controls="open-access-articles-tab" id="open-access-articles" class="event_tabs" tabindex="-1"> Open Access </button> </div>   <div tabindex="0" role="tabpanel" id="most-read-tab" aria-labelledby="most-read" hidden="hidden"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Most read</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/acead2" class="art-list-item-title event_main-link">The 2023 wearable photoplethysmography roadmap</a> <p class="small art-list-item-meta"> Peter H Charlton <em>et al</em> 2023 <em>Physiol. Meas.</em> <b>44</b> 111001 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="The 2023 wearable photoplethysmography roadmap" data-link-purpose-append-open="The 2023 wearable photoplethysmography roadmap">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/acead2/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, The 2023 wearable photoplethysmography roadmap</span></a> <a href="/article/10.1088/1361-6579/acead2/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, The 2023 wearable photoplethysmography roadmap</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/acead2">https://doi.org/10.1088/1361-6579/acead2</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ab840a" class="art-list-item-title event_main-link">Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG</a> <p class="small art-list-item-meta"> Hannu Kinnunen <em>et al</em> 2020 <em>Physiol. Meas.</em> <b>41</b> 04NT01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG" data-link-purpose-append-open="Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ab840a/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG</span></a> <a href="/article/10.1088/1361-6579/ab840a/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Feasible assessment of recovery and cardiovascular health: accuracy of nocturnal HR and HRV assessed via ring PPG in comparison to medical grade ECG</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>: To validate the accuracy of the Oura ring in the quantification of resting heart rate (HR) and heart rate variability (HRV). <i>Background</i>: Wearable devices have become comfortable, lightweight, and technologically advanced for assessing health behavior. As an example, the novel Oura ring integrates daily physical activity and nocturnal cardiovascular measurements. Ring users can follow their autonomic nervous system responses to their daily behavior based on nightly changes in HR and HRV, and adjust their behavior accordingly after self-reflection. As wearable photoplethysmogram (PPG) can be disrupted by several confounding influences, it is crucial to demonstrate the accuracy of ring measurements. <i>Approach</i>: Nocturnal HR and HRV were assessed in 49 adults with simultaneous measurements from the Oura ring and the gold standard ECG measurement. Female and male participants with a wide age range (15–72 years) and physical activity status were included. Regression analysis between ECG and the ring outcomes was performed. <i>Main results</i>: Very high agreement between the ring and ECG was observed for nightly average HR and HRV (r<sup>2</sup> = 0.996 and 0.980, respectively) with a mean bias of −0.63 bpm and −1.2 ms. High agreement was also observed across 5 min segments within individual nights in (r<sup>2</sup> = 0.869 ± 0.098 and 0.765 ± 0.178 in HR and HRV, respectively). <i>Significance</i>: Present findings indicate high validity of the Oura ring in the assessment of nocturnal HR and HRV in healthy adults. The results show the utility of this miniaturised device as a lifestyle management tool in long-term settings. High quality PPG signal results prompt future studies utilizing ring PPG towards clinically relevant health outcomes.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ab840a">https://doi.org/10.1088/1361-6579/ab840a</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ab299e" class="art-list-item-title event_main-link">Recent development of respiratory rate measurement technologies</a> <p class="small art-list-item-meta"> Haipeng Liu <em>et al</em> 2019 <em>Physiol. Meas.</em> <b>40</b> 07TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Recent development of respiratory rate measurement technologies" data-link-purpose-append-open="Recent development of respiratory rate measurement technologies">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ab299e/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Recent development of respiratory rate measurement technologies</span></a> <a href="/article/10.1088/1361-6579/ab299e/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Recent development of respiratory rate measurement technologies</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Respiratory rate (RR) is an important physiological parameter whose abnormality has been regarded as an important indicator of serious illness. In order to make RR monitoring simple to perform, reliable and accurate, many different methods have been proposed for such automatic monitoring. According to the theory of respiratory rate extraction, methods are categorized into three modalities: extracting RR from other physiological signals, RR measurement based on respiratory movements, and RR measurement based on airflow. The merits and limitations of each method are highlighted and discussed. In addition, current works are summarized to suggest key directions for the development of future RR monitoring methodologies.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ab299e">https://doi.org/10.1088/1361-6579/ab299e</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad33a2" class="art-list-item-title event_main-link">pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis</a> <p class="small art-list-item-meta"> Márton Á Goda <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 045001 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis" data-link-purpose-append-open="pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad33a2/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis</span></a> <a href="/article/10.1088/1361-6579/ad33a2/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, pyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Photoplethysmography is a non-invasive optical technique that measures changes in blood volume within tissues. It is commonly and being increasingly used for a variety of research and clinical applications to assess vascular dynamics and physiological parameters. Yet, contrary to heart rate variability measures, a field which has seen the development of stable standards and advanced toolboxes and software, no such standards and limited open tools exist for continuous photoplethysmogram (PPG) analysis. Consequently, the primary objective of this research was to identify, standardize, implement and validate key digital PPG biomarkers. <i>Approach.</i> This work describes the creation of a standard Python toolbox, denoted <i>pyPPG</i>, for long-term continuous PPG time-series analysis and demonstrates the detection and computation of a high number of fiducial points and digital biomarkers using a standard fingerbased transmission pulse oximeter. <i>Main results.</i> The improved PPG peak detector had an F1-score of 88.19% for the state-of-the-art benchmark when evaluated on 2054 adult polysomnography recordings totaling over 91 million reference beats. The algorithm outperformed the open-source original Matlab implementation by ∼5% when benchmarked on a subset of 100 randomly selected MESA recordings. More than 3000 fiducial points were manually annotated by two annotators in order to validate the fiducial points detector. The detector consistently demonstrated high performance, with a mean absolute error of less than 10 ms for all fiducial points. <i>Significance.</i> Based on these fiducial points, <i>pyPPG</i> engineered a set of 74 PPG biomarkers. Studying PPG time-series variability using <i>pyPPG</i> can enhance our understanding of the manifestations and etiology of diseases. This toolbox can also be used for biomarker engineering in training data-driven models. <i>pyPPG</i> is available on <a href="https://physiozoo.com/">https://physiozoo.com/</a>.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad33a2">https://doi.org/10.1088/1361-6579/ad33a2</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/aa60b9" class="art-list-item-title event_main-link">Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue</a> <p class="small art-list-item-meta"> Gazzoni Marco <em>et al</em> 2017 <em>Physiol. Meas.</em> <b>38</b> R27 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue" data-link-purpose-append-open="Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/aa60b9/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue</span></a> <a href="/article/10.1088/1361-6579/aa60b9/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>In a broad view, fatigue is used to indicate a degree of weariness. On a muscular level, fatigue posits the reduced capacity of muscle fibres to produce force, even in the presence of motor neuron excitation via either spinal mechanisms or electric pulses applied externally. Prior to decreased force, when sustaining physically demanding tasks, alterations in the muscle electrical properties take place. These alterations, termed <i>myoelectric manifestation of fatigue</i>, can be assessed non-invasively with a pair of surface electrodes positioned appropriately on the target muscle; <i>traditional approach</i>. A relatively more recent approach consists of the use of multiple electrodes. This <i>multi-channel approach</i> provides access to a set of physiologically relevant variables on the global muscle level or on the level of single motor units, opening new fronts for the study of muscle fatigue; it allows for: (i) a more precise quantification of the propagation velocity, a physiological variable of marked interest to the study of fatigue; (ii) the assessment of regional, myoelectric manifestations of fatigue; (iii) the analysis of single motor units, with the possibility to obtain information about motor unit control and fibre membrane changes. This review provides a methodological account on the <i>multi-channel approach</i> for the study of <i>myoelectric manifestation of fatigue</i> and on the experimental conditions to which it applies, as well as examples of their current applications.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/aa60b9">https://doi.org/10.1088/1361-6579/aa60b9</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/aa6782" class="art-list-item-title event_main-link">An introduction into autonomic nervous function</a> <p class="small art-list-item-meta"> John M Karemaker 2017 <em>Physiol. Meas.</em> <b>38</b> R89 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="An introduction into autonomic nervous function" data-link-purpose-append-open="An introduction into autonomic nervous function">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/aa6782/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, An introduction into autonomic nervous function</span></a> <a href="/article/10.1088/1361-6579/aa6782/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, An introduction into autonomic nervous function</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The results of many medical measurements are directly or indirectly influenced by the autonomic nervous system (ANS). For example pupil size or heart rate may demonstrate striking moment-to-moment variability. This review intends to elucidate the physiology behind this seemingly unpredictable system.</p><p>The review is split up into: 1. The peripheral ANS, parallel innervation by the sympathetic and parasympathetic branches, their transmitters and co-transmitters. It treats questions like the supposed sympatho/vagal balance, organization in plexuses and the 'little brains' that are active like in the enteric system or around the heart. Part 2 treats ANS-function in some (example-) organs in more detail: the eye, the heart, blood vessels, lungs, respiration and cardiorespiratory coupling. Part 3 poses the question of who is directing what? Is the ANS a strictly top-down directed system or is its organization bottom-up? Finally, it is concluded that the 'noisy numbers' in medical measurements, caused by ANS variability, are part and parcel of how the system works. This topical review is a one-man's undertaking and may possibly give a biased view. The author has explicitly indicated in the text where his views are not (yet) supported by facts, hoping to provoke discussion and instigate new research.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/aa6782">https://doi.org/10.1088/1361-6579/aa6782</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad4954" class="art-list-item-title event_main-link">ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization</a> <p class="small art-list-item-meta"> Kshama Kodthalu Shivashankara <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 055019 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization" data-link-purpose-append-open="ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad4954/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization</span></a> <a href="/article/10.1088/1361-6579/ad4954/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, ECG-Image-Kit: a synthetic image generation toolbox to facilitate deep learning-based electrocardiogram digitization</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Cardiovascular diseases are a major cause of mortality globally, and electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored in printed formats. However, these printouts, even when scanned, are incompatible with advanced ECG diagnosis software that require time-series data. Digitizing ECG images is vital for training machine learning models in ECG diagnosis, leveraging the extensive global archives collected over decades. Deep learning models for image processing are promising in this regard, although the lack of clinical ECG archives with reference time-series data is challenging. Data augmentation techniques using realistic generative data models provide a solution. <i>Approach.</i> We introduce <i>ECG-Image-Kit</i>, an open-source toolbox for generating synthetic multi-lead ECG images with realistic artifacts from time-series data, aimed at automating the conversion of scanned ECG images to ECG data points. The tool synthesizes ECG images from real time-series data, applying distortions like text artifacts, wrinkles, and creases on a standard ECG paper background. <i>Main results.</i> As a case study, we used ECG-Image-Kit to create a dataset of 21 801 ECG images from the PhysioNet QT database. We developed and trained a combination of a traditional computer vision and deep neural network model on this dataset to convert synthetic images into time-series data for evaluation. We assessed digitization quality by calculating the signal-to-noise ratio and compared clinical parameters like QRS width, RR, and QT intervals recovered from this pipeline, with the ground truth extracted from ECG time-series. The results show that this deep learning pipeline accurately digitizes paper ECGs, maintaining clinical parameters, and highlights a generative approach to digitization. <i>Significance.</i> The toolbox has broad applications, including model development for ECG image digitization and classification. The toolbox currently supports data augmentation for the 2024 PhysioNet Challenge, focusing on digitizing and classifying paper ECG images.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad4954">https://doi.org/10.1088/1361-6579/ad4954</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/acd51a" class="art-list-item-title event_main-link">A review of the effect of skin pigmentation on pulse oximeter accuracy</a> <p class="small art-list-item-meta"> Raghda Al-Halawani <em>et al</em> 2023 <em>Physiol. Meas.</em> <b>44</b> 05TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="A review of the effect of skin pigmentation on pulse oximeter accuracy" data-link-purpose-append-open="A review of the effect of skin pigmentation on pulse oximeter accuracy">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/acd51a/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, A review of the effect of skin pigmentation on pulse oximeter accuracy</span></a> <a href="/article/10.1088/1361-6579/acd51a/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, A review of the effect of skin pigmentation on pulse oximeter accuracy</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. Pulse oximetry is a non-invasive optical technique used to measure arterial oxygen saturation (SpO<sub>2</sub>) in a variety of clinical settings and scenarios. Despite being one the most significant technological advances in health monitoring over the last few decades, there have been reports on its various limitations. Recently due to the Covid-19 pandemic, questions about pulse oximeter technology and its accuracy when used in people with different skin pigmentation have resurfaced, and are to be addressed. <i>Approach</i>. This review presents an introduction to the technique of pulse oximetry including its basic principle of operation, technology, and limitations, with a more in depth focus on skin pigmentation. Relevant literature relating to the performance and accuracy of pulse oximeters in populations with different skin pigmentation are evaluated.<i> Main Results</i>. The majority of the evidence suggests that the accuracy of pulse oximetry differs in subjects of different skin pigmentations to a level that requires particular attention, with decreased accuracy in patients with dark skin. <i>Significance</i>. Some recommendations, both from the literature and contributions from the authors, suggest how future work could address these inaccuracies to potentially improve clinical outcomes. These include the objective quantification of skin pigmentation to replace currently used qualitative methods, and computational modelling for predicting calibration algorithms based on skin colour.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/acd51a">https://doi.org/10.1088/1361-6579/acd51a</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ac826d" class="art-list-item-title event_main-link">Detecting beats in the photoplethysmogram: benchmarking open-source algorithms</a> <p class="small art-list-item-meta"> Peter H Charlton <em>et al</em> 2022 <em>Physiol. Meas.</em> <b>43</b> 085007 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Detecting beats in the photoplethysmogram: benchmarking open-source algorithms" data-link-purpose-append-open="Detecting beats in the photoplethysmogram: benchmarking open-source algorithms">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ac826d/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Detecting beats in the photoplethysmogram: benchmarking open-source algorithms</span></a> <a href="/article/10.1088/1361-6579/ac826d/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Detecting beats in the photoplethysmogram: benchmarking open-source algorithms</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The photoplethysmogram (PPG) signal is widely used in pulse oximeters and smartwatches. A fundamental step in analysing the PPG is the detection of heartbeats. Several PPG beat detection algorithms have been proposed, although it is not clear which performs best. <i>Objective:</i> This study aimed to: (i) develop a framework with which to design and test PPG beat detectors; (ii) assess the performance of PPG beat detectors in different use cases; and (iii) investigate how their performance is affected by patient demographics and physiology. <i>Approach:</i> Fifteen beat detectors were assessed against electrocardiogram-derived heartbeats using data from eight datasets. Performance was assessed using the <i>F</i><sub>1</sub> score, which combines sensitivity and positive predictive value. <i>Main results:</i> Eight beat detectors performed well in the absence of movement with <i>F</i><sub>1</sub> scores of ≥90% on hospital data and wearable data collected at rest. Their performance was poorer during exercise with <i>F</i><sub>1</sub> scores of 55%–91%; poorer in neonates than adults with <i>F</i><sub>1</sub> scores of 84%–96% in neonates compared to 98%–99% in adults; and poorer in atrial fibrillation (AF) with <i>F</i><sub>1</sub> scores of 92%–97% in AF compared to 99%–100% in normal sinus rhythm. <i>Significance:</i> Two PPG beat detectors denoted 'MSPTD' and 'qppg' performed best, with complementary performance characteristics. This evidence can be used to inform the choice of PPG beat detector algorithm. The algorithms, datasets, and assessment framework are freely available.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ac826d">https://doi.org/10.1088/1361-6579/ac826d</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/0967-3334/28/3/R01" class="art-list-item-title event_main-link">Photoplethysmography and its application in clinical physiological measurement</a> <p class="small art-list-item-meta"> John Allen 2007 <em>Physiol. Meas.</em> <b>28</b> R1 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Photoplethysmography and its application in clinical physiological measurement" data-link-purpose-append-open="Photoplethysmography and its application in clinical physiological measurement">Open abstract</span> </button> <a href="/article/10.1088/0967-3334/28/3/R01/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Photoplethysmography and its application in clinical physiological measurement</span></a> <a href="/article/10.1088/0967-3334/28/3/R01/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Photoplethysmography and its application in clinical physiological measurement</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non-invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile ('AC') physiological waveform attributed to cardiac synchronous changes in the blood volume with each heart beat, and is superimposed on a slowly varying ('DC') baseline with various lower frequency components attributed to respiration, sympathetic nervous system activity and thermoregulation. Although the origins of the components of the PPG signal are not fully understood, it is generally accepted that they can provide valuable information about the cardiovascular system. There has been a resurgence of interest in the technique in recent years, driven by the demand for low cost, simple and portable technology for the primary care and community based clinical settings, the wide availability of low cost and small semiconductor components, and the advancement of computer-based pulse wave analysis techniques. The PPG technology has been used in a wide range of commercially available medical devices for measuring oxygen saturation, blood pressure and cardiac output, assessing autonomic function and also detecting peripheral vascular disease. The introductory sections of the topical review describe the basic principle of operation and interaction of light with tissue, early and recent history of PPG, instrumentation, measurement protocol, and pulse wave analysis. The review then focuses on the applications of PPG in clinical physiological measurements, including clinical physiological monitoring, vascular assessment and autonomic function.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/0967-3334/28/3/R01">https://doi.org/10.1088/0967-3334/28/3/R01</a> </div> </div> </div> </div> </div>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="latest-articles-tab" aria-labelledby="latest-articles"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Latest articles</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad9233" class="art-list-item-title event_main-link">Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches</a> <p class="small art-list-item-meta"> Luiz E V Silva <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115005 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches" data-link-purpose-append-open="Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9233/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches</span></a> <a href="/article/10.1088/1361-6579/ad9233/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Amplitude Spectrum Area (AMSA) of the electrocardiogram (ECG) waveform during ventricular fibrillation (VF) has shown promise as a predictor of defibrillation success during cardiopulmonary resuscitation (CPR). However, AMSA relies on the magnitude of the ECG waveform, raising concerns about reproducibility across different settings that may introduce magnitude bias. This study aimed to evaluate different AMSA normalization approaches and their impact on removing bias while preserving predictive value. <i>Approach.</i> ECG were recorded in 118 piglets (1–2 months old) during a model of asphyxia-associated VF cardiac arrest and CPR. An initial subset (91/118) was recorded using one device (Device 1), and the remaining piglets were recorded in the second device (Device 2). Raw AMSA and three ECG magnitude metrics were estimated to assess magnitude-related bias between devices. Five AMSA normalization approaches were assessed for their ability to remove detected bias and to classify defibrillation success. <i>Main results.</i> Device 2 showed significantly lower ECG magnitude and raw AMSA compared to Device 1. CPR-based AMSA normalization approaches mitigated device-associated bias. Raw AMSA normalized by the average AMSA in the 1st minute of CPR (AMSA<sub>1m-cpr</sub>) exhibited the best sensitivity and specificity for classification of successful and unsuccessful defibrillation. While the optimal AMSA<sub>1m-cpr</sub> thresholds for balanced sensitivity and specificity were consistent across both devices, the optimal raw AMSA thresholds varied between the two devices. The area under the receiver operating characteristic curve for AMSA<sub>1m-cpr</sub> did not significantly differ from raw AMSA for both devices (Device 1: 0.74 vs. 0.88, <i>P</i> = 0.14; Device 2: 0.56 vs. 0.59, <i>P</i> = 0.81). <i>Significance.</i> Unlike raw AMSA, AMSA<sub>1m-cpr</sub> demonstrated consistent results across different devices while maintaining predictive value for defibrillation success. This consistency has important implications for the widespread use of AMSA and the development of future guidelines on optimal AMSA thresholds for successful defibrillation.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9233">https://doi.org/10.1088/1361-6579/ad9233</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9234" class="art-list-item-title event_main-link">Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</a> <p class="small art-list-item-meta"> Marta Iovino <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115004 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices" data-link-purpose-append-open="Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9234/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</span></a> <a href="/article/10.1088/1361-6579/ad9234/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> This study evaluates the effectiveness of four machine learning algorithms in classifying physiological stress using heart rate variability (HRV) and pulse rate variability (PRV) time series, comparing an automatic feature selection based on Akaike's criterion to a physiologically-based feature selection approach. <i>Approach.</i> Linear discriminant analysis, support vector machines, <i>K</i>-nearest neighbors and random forest were applied on ten HRV and PRV indices from time, frequency and information domains, selected with the two feature selection approaches. Data were collected from 127 healthy individuals during different stress conditions (rest, postural and mental stress). <i>Main results.</i> Our results highlight that, while specific stress classification is feasible, distinguishing between postural and mental stress remains challenging. The used classifiers exhibited similar performance, with automatic Akaike Information Criterion-based feature selection proving overall better than the physiology-driven approach. Additionally, PRV-based features performed comparably to HRV-based ones, indicating their potential in outpatient monitoring using wearable devices. <i>Significance.</i> The obtained findings help to determine the most relevant HRV/PRV features for stress classification, potentially useful to highlight different physiological mechanisms involved during both challenges accompanied by a shift in the sympathovagal balance. The proposed approach may have implications for advancing stress assessment methodologies in clinical settings and real-world contexts for well-being evaluation.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9234">https://doi.org/10.1088/1361-6579/ad9234</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad8da4" class="art-list-item-title event_main-link">Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable</a> <p class="small art-list-item-meta"> Anne-Christianne Kentgens <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115003 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable" data-link-purpose-append-open="Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad8da4/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable</span></a> <a href="/article/10.1088/1361-6579/ad8da4/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Sulfur hexafluoride (SF<sub>6</sub>) multiple-breath washout (MBW) assesses ventilation inhomogeneity, as an early marker of obstructive respiratory diseases. Primary outcomes are customarily washout-derived, and it is unclear whether the preceding SF<sub>6</sub>-washin can provide similar estimates. We aimed to assess comparability of primary SF<sub>6</sub>-MBW outcomes between washin and washout phases of infant SF<sub>6</sub>-MBW data measured with the WBreath (ndd Medizintechnik AG, Zurich, Switzerland) and Spiroware (Eco Medics AG, Duernten, Switzerland) MBW-setups, respectively. <i>Approach.</i> We assessed mean relative differences in lung clearance index (LCI) and functional residual capacity (FRC) between the washin and washout of existing SF<sub>6</sub>-MBW data from healthy infants and infants with cystic fibrosis (CF). We assessed whether these differences exceeded the mean relative within-test between-trial differences of washout-derived outcomes, which can be attributed to natural variability. We also explored non-physiological factors using a pediatric lung simulator. <i>Main results.</i> LCI and FRC from washin and washout were not comparable, for both setups. The mean difference (SD) in LCI between washin and washout was 2.3(10.8)% for WBreath and −9.7(8.0)% for Spiroware, while in FRC it was −4.7(8.4)% for WBreath and −2.3(9.7)% for Spiroware. These differences exceeded the within-test between-trial differences in washout-derived outcomes. Outcomes from washin and washout were also not comparable in a pediatric lung simulator. <i>Significance.</i> Outcomes of the washin and washout were not comparable due to an interplay of physiological and non-physiological factors, and cannot be used interchangeably.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad8da4">https://doi.org/10.1088/1361-6579/ad8da4</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad8f29" class="art-list-item-title event_main-link">Assessment of arteriosclerosis based on lognormal fitting</a> <p class="small art-list-item-meta"> Hao Tang <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115001 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Assessment of arteriosclerosis based on lognormal fitting" data-link-purpose-append-open="Assessment of arteriosclerosis based on lognormal fitting">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad8f29/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Assessment of arteriosclerosis based on lognormal fitting</span></a> <a href="/article/10.1088/1361-6579/ad8f29/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Assessment of arteriosclerosis based on lognormal fitting</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. Pulse pressure waves contain information about human physiology. There is a need for a simple, accurate way to know cardiovascular health in the clinic, so as to realize the implementation of convenient and effective early health monitoring for patients with arteriosclerosis. <i>Approach</i>. This study proposes an arteriosclerosis assessment method based on fitting a lognormal function, along with improving a conventional electronic sphygmomanometer. During the deflation phase of blood pressure measurement, the cuff pressure was kept constant (40 mmHg) and an additional 10 s of pulse signal was acquired. To derive the pulse pressure waveforms for a single cycle, the acquired pulse data of 101 cases were preprocessed in this study, including filtering for noise removal, onset point identification, removal of baseline drift, and normalization. In this study, an improved pulse resolution algorithm is proposed for the multimodal problem of the pulse wave, combining waveform matching and threshold setting, and finally obtaining the resolution parameters of the lognormal function with an average error less than 1.5%. <i>Main results</i>. According to the correlation analysis, the resolved parameters <i>A</i><sub>1</sub>, <i>W</i><sub>2</sub>, <i>C</i><sub>2</sub>, <i>W</i><sub>3</sub>, and <i>C</i><sub>3</sub> were significantly correlated with brachial-ankle Pulse Wave Velocity, and the absolute correlation range in 0.17–0.53, which can be used as a reference index for arteriosclerosis. An arteriosclerosis assessment model was constructed based on the support vector mechanism, and the prediction accuracy was 91.1%. <i>Significance</i>. This study provides a new solution idea for the arteriosclerosis assessment method as well as the pulse resolution algorithm, which has a greater reference value.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad8f29">https://doi.org/10.1088/1361-6579/ad8f29</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad8f8f" class="art-list-item-title event_main-link">Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</a> <p class="small art-list-item-meta"> Karen McCloy <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115002 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography" data-link-purpose-append-open="Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad8f8f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</span></a> <a href="/article/10.1088/1361-6579/ad8f8f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Obstructive sleep apnea (OSA) is associated with deficits in vigilance. This work explored the temporal patterns of OSA-related events during sleep and vigilance levels measured by the psychomotor vigilance test (PVT) in patients undergoing polysomnography (PSG) for suspected OSA. <i>Approach.</i> The PVT was conducted prior to in-laboratory PSG for 80 patients suspected of having OSA. Three groups were formed based on PVT-RT-outcomes and participants were randomly allocated into Training (<i>n</i> = 55) and Test (<i>n</i> = 25) samples. Sleep epochs of non-rapid-eye movement (NREM) electroencephalographic (EEG) asynchrony data, and REM and NREM data for respiratory, arousal, limb movement and desaturation events were analysed. The data were segmented by sleep stage, by sleep blocks (SB) of stable Stage N2, Stage N3, mixed-stage NREM sleep (NXL), and, by Time of Night (TN) across sleep. Models associating this data with PVT groups were developed and tested. <i>Main Results.</i><b>A</b> model using NREM EEG asynchrony data segmented by SB and TN achieved 81.9% accuracy in the Test Cohort. Models based on interhemispheric asynchrony SB data and OSA data segmented by TN achieved 80.6% and 79.5% respectively. <i>Significance.</i> Novel data segmentation methods via blocks of NXL and TN have improved our understanding of the relationship between sleep, OSA and vigilance.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad8f8f">https://doi.org/10.1088/1361-6579/ad8f8f</a> </div> </div> </div> </div> </div>  </div> </div> </div>     <div tabindex="0" role="tabpanel" id="review-articles-tab" aria-labelledby="review-articles" hidden="hidden"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Review articles</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad838d" class="art-list-item-title event_main-link">Survey on portable sensing technologies for the radial artery characterization</a> <p class="small art-list-item-meta"> Aurélia Leandri <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 10TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Survey on portable sensing technologies for the radial artery characterization" data-link-purpose-append-open="Survey on portable sensing technologies for the radial artery characterization">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad838d/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Survey on portable sensing technologies for the radial artery characterization</span></a> <a href="/article/10.1088/1361-6579/ad838d/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Survey on portable sensing technologies for the radial artery characterization</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>The radial artery, one of the terminal branches of the forearm, is utilized for vascular access and in various non-invasive measurement method, providing crucial medical insights. Various sensor technologies have been developed, each suited to specific characterization requirements. The work presented in this paper is based on a systematic literature review of the main publications relating to this topic. Analysis of the forearm vascular system complex array of anatomical structures shows that the radial artery can be characterized by its size, position, elasticity, tissue evaluation, blood flow and blood composition. The survey of medical procedures for patient monitoring, diagnosis and pre-operative validation shows the use of measures for pulse wave, blood pressure, heart rate, skin temperature, tissue response,<span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0967-3334/45/10/10TR01/revision2/pmeaad838dieqn1.gif" style="max-width: 100%;" alt="$\ldots$" align="top"></img></span><script type="math/tex">\ldots</script></span></span> By exploring sensor technologies used for artery characterization, we produce a synthesis of measurement principles, measured phenomena and measurement accuracy for capacitive, piezoresistive, bioimpedance, thermography, fiber optic based, piezoelectric and photoacoustic sensors. A comparative study is conducted for sensor technologies by considering the metrics of the information to be collected and the associated accuracy as well as the portability, the complexity of the processing, the cost and the mode of contact with the arm. Finally, a comprehensive framework is proposed to facilitate informed decisions in the development of medical devices tailored to specific characterization needs.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad838d">https://doi.org/10.1088/1361-6579/ad838d</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad7348" class="art-list-item-title event_main-link">Progression of total training volume in resistance training studies and its application to skeletal muscle growth</a> <p class="small art-list-item-meta"> William B Hammert <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 08TR03 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Progression of total training volume in resistance training studies and its application to skeletal muscle growth" data-link-purpose-append-open="Progression of total training volume in resistance training studies and its application to skeletal muscle growth">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad7348/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Progression of total training volume in resistance training studies and its application to skeletal muscle growth</span></a> <a href="/article/10.1088/1361-6579/ad7348/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Progression of total training volume in resistance training studies and its application to skeletal muscle growth</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Progressive overload describes the gradual increase of stress placed on the body during exercise training, and is often quantified (i.e. in resistance training studies) through increases in total training volume (i.e. sets <b>×</b> repetitions <b>×</b> load) from the first to final week of the exercise training intervention. Within the literature, it has become increasingly common for authors to discuss skeletal muscle growth adaptations in the context of increases in total training volume (i.e. the magnitude progression in total training volume). The present manuscript discusses a physiological rationale for progressive overload and then explains why, in our opinion, quantifying the progression of total training volume within research investigations tells very little about muscle growth adaptations to resistance training. Our opinion is based on the following research findings: (1) a noncausal connection between increases in total training volume (i.e. progressively overloading the resistance exercise stimulus) and increases in skeletal muscle size; (2) similar changes in total training volume may not always produce similar increases in muscle size; and (3) the ability to exercise more and consequently amass larger increases in total training volume may not inherently produce more skeletal muscle growth. The methodology of quantifying changes in total training volume may therefore provide a means through which researchers can mathematically determine the total amount of external 'work' performed within a resistance training study. It may not, however, always explain muscle growth adaptations.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad7348">https://doi.org/10.1088/1361-6579/ad7348</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad6be4" class="art-list-item-title event_main-link">Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review</a> <p class="small art-list-item-meta"> Kai Li and Jiuai Sun 2024 <em>Physiol. Meas.</em> <b>45</b> 08TR02 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review" data-link-purpose-append-open="Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad6be4/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review</span></a> <a href="/article/10.1088/1361-6579/ad6be4/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Understanding the physiological transmission mechanisms of photoplethysmography signals: a comprehensive review</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. The widespread adoption of Photoplethysmography (PPG) as a non-invasive method for detecting blood volume variations and deriving vital physiological parameters reflecting health status has surged, primarily due to its accessibility, cost-effectiveness, and non-intrusive nature. This has led to extensive research around this technique in both daily life and clinical applications. Interestingly, despite the existence of contradictory explanations of the underlying mechanism of PPG signals across various applications, a systematic investigation into this crucial matter has not been conducted thus far. This gap in understanding hinders the full exploitation of PPG technology and undermines its accuracy and reliability in numerous applications. <i>Approach</i>. Building upon a comprehensive review of the fundamental principles and technological advancements in PPG, this paper initially attributes the origin of PPG signals to a combination of physical and physiological transmission processes. Furthermore, three distinct models outlining the concerned physiological transmission processes are synthesized, with each model undergoing critical examination based on theoretical underpinnings, empirical evidence, and constraints. <i>Significance</i>. The ultimate objective is to form a fundamental framework for a better understanding of physiological transmission processes in PPG signal generation and to facilitate the development of more reliable technologies for detecting physiological signals.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad6be4">https://doi.org/10.1088/1361-6579/ad6be4</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad6acf" class="art-list-item-title event_main-link">The role of pulse wave analysis indexes for critically ill patients: a narrative review</a> <p class="small art-list-item-meta"> Marta Carrara <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 08TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="The role of pulse wave analysis indexes for critically ill patients: a narrative review" data-link-purpose-append-open="The role of pulse wave analysis indexes for critically ill patients: a narrative review">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad6acf/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, The role of pulse wave analysis indexes for critically ill patients: a narrative review</span></a> <a href="/article/10.1088/1361-6579/ad6acf/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, The role of pulse wave analysis indexes for critically ill patients: a narrative review</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Arterial pulse wave analysis (PWA) is now established as a powerful tool to investigate the cardiovascular system, and several clinical studies have shown how PWA can provide valuable prognostic information over and beyond traditional cardiovascular risk factors. Typically these techniques are applied to chronic conditions, such as hypertension or aging, to monitor the slow structural changes of the vascular system which lead to important alterations of the arterial PW. However, their application to acute critical illness is not currently widespread, probably because of the high hemodynamic instability and acute dynamic alterations affecting the cardiovascular system of these patients. <i>Approach.</i> In this work we propose a review of the physiological and methodological basis of PWA, describing how it can be used to provide insights into arterial structure and function, cardiovascular biomechanical properties, and to derive information on wave propagation and reflection. <i>Main results.</i> The applicability of these techniques to acute critical illness, especially septic shock, is extensively discussed, highlighting the feasibility of their use in acute critical patients and their role in optimizing therapy administration and hemodynamic monitoring. <i>Significance.</i> The potential for the clinical use of these techniques lies in the ease of computation and availability of arterial blood pressure signals, as invasive arterial lines are commonly used in these patients. We hope that the concepts illustrated in the present review will soon be translated into clinical practice.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad6acf">https://doi.org/10.1088/1361-6579/ad6acf</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad45aa" class="art-list-item-title event_main-link">Accelerometer techniques for capturing human movement validated against direct observation: a scoping review</a> <p class="small art-list-item-meta"> Elyse Letts <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 07TR01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Accelerometer techniques for capturing human movement validated against direct observation: a scoping review" data-link-purpose-append-open="Accelerometer techniques for capturing human movement validated against direct observation: a scoping review">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad45aa/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Accelerometer techniques for capturing human movement validated against direct observation: a scoping review</span></a> <a href="/article/10.1088/1361-6579/ad45aa/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Accelerometer techniques for capturing human movement validated against direct observation: a scoping review</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Accelerometers are devices commonly used to measure human physical activity and sedentary time. Accelerometer capabilities and analytical techniques have evolved rapidly, making it difficult for researchers to keep track of advances and best practices for data processing and analysis. The objective of this scoping review is to determine the existing methods for analyzing accelerometer data for capturing human movement which have been validated against the criterion measure of direct observation. <i>Approach.</i> This scoping review searched 14 academic and 5 grey databases. Two independent raters screened by title and abstract, then full text. Data were extracted using Microsoft Excel and checked by an independent reviewer. <i>Main</i><i>results.</i> The search yielded 1039 papers and the final analysis included 115 papers. A total of 71 unique accelerometer models were used across a total of 4217 participants. While all studies underwent validation from direct observation, most direct observation occurred live (55%) or using recordings (42%). Analysis techniques included machine learning (ML) approaches (22%), the use of existing cut-points (18%), receiver operating characteristic curves to determine cut-points (14%), and other strategies including regressions and non-ML algorithms (8%). <i>Significance.</i> ML techniques are becoming more prevalent and are often used for activity identification. Cut-point methods are still frequently used. Activity intensity is the most assessed activity outcome; however, both the analyses and outcomes assessed vary by wear location. This scoping review provides a comprehensive overview of accelerometer analysis and validation techniques using direct observation and is a useful tool for researchers using accelerometers.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad45aa">https://doi.org/10.1088/1361-6579/ad45aa</a> </div> </div> </div> </div> </div>  </div> </div> </div>       <div tabindex="0" role="tabpanel" id="accepted-manuscripts-tab" aria-labelledby="accepted-manuscripts" hidden="hidden"> <div class="reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Accepted manuscripts</button> </h2> <div class="reveal-content tabpanel__content" style="display: none;">  <p id="jnl-issue-disp-links" class="cf"> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab">Open all abstracts<span class="offscreen-hidden">, in this tab</span></button> </p>  <div class="art-list" id="wd-jnl-issue-art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9798" class="art-list-item-title event_main-link">Telephone training to improve ECG quality in remote screening for atrial fibrillation</a> <p class="small art-list-item-meta"> Prathivadi Bhayankaram et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Telephone training to improve ECG quality in remote screening for atrial fibrillation" data-link-purpose-append-open="Telephone training to improve ECG quality in remote screening for atrial fibrillation">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9798/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Telephone training to improve ECG quality in remote screening for atrial fibrillation</span></a> <a href="/article/10.1088/1361-6579/ad9798/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Telephone training to improve ECG quality in remote screening for atrial fibrillation</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective:&#xD;Self-recorded, single-lead ECGs are increasingly used to diagnose arrhythmias. However, they can be of variable quality, affecting the reliability of interpretation. In this analysis of ECGs collected in atrial fibrillation screening studies, our aims were to: (i) determine the quality of ECGs when recorded unsupervised; and (ii) investigate whether telephone training improved ECG quality.&#xD;&#xD;Approach:&#xD;Data was obtained from the Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) programme, where participants recorded four single-lead ECG traces per day for three weeks using a handheld device. ECG quality was assessed by an automated algorithm, and participants who recorded >25% poor-quality ECGs from days 4-10 of screening were identified for training to improve ECG recording technique. Training was delivered when research team capacity permitted.&#xD;&#xD;Main results:&#xD;13,741 participants recorded 1,127,264 ECGs, of which 41,288 (3.7%) were poor-quality. Most participants (51.5%) didn't record any poor-quality ECGs. 1,088 (7.9%) participants met the threshold for training. Of these, 165 participants received training and 923 didn't. The median proportion of poor-quality ECGs per participant on days 1-3 was 41.7 (27.3-50.0) % for those who received training and 33.3 (25.0-45.5) % for those who didn't. On days 11-21, the median proportions of poor-quality ECGs per participant were significantly lower (p<0.001) for those who received training, 17.8 (5.0-31.6) %, and those who didn't, 14.0 (4.8-30.2) %. Comparing these groups, the mean (95% confidence interval) reduction in proportion of poor-quality ECGs from days 1-3 to days 11-21 was 20.2 (16.8-23.5) % in those who received training and 16.0 (14.7-17.3) % in those who didn't (p=0.396). &#xD;&#xD;Significance:&#xD;Most participants achieved adequate quality ECGs. For those that didn't, ECG quality improved over time regardless of whether they received telephone training. Telephone training may therefore not be required to achieve improvements in ECG quality during screening.&#xD;</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9798">https://doi.org/10.1088/1361-6579/ad9798</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9683" class="art-list-item-title event_main-link">Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</a> <p class="small art-list-item-meta"> Gallego Vazquez et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber" data-link-purpose-append-open="Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9683/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</span></a> <a href="/article/10.1088/1361-6579/ad9683/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Increasing temperatures pose new challenges for track workers, who endure prolonged exposure to extreme heat and humidity. New methods are critically needed to assess their performance and heat tolerance, aiming to mitigate workplace accidents and long-term health consequences. This study aimed to investigate the physiological effects of heat exposure on track workers, using wearable sensors to monitor key physiological parameters under controlled environmental conditions. Nineteen track workers participated in the study, which included two experimental sessions simulating different thermal environments: a typical Swiss summer night and a hot summer day. Participants' core body temperature, heart rate (HR), and skin temperature were monitored using wearable sensors, and physiological indexes were computed. In addition, Perceptual Strain Index (PeSI) and Psychomotor Vigilance Task (PVT) response times were recorded. Statistically significant increases in physiological parameters were observed under hotter conditions. The study identified statistically significant correlations between the PeSI and the PSI and between PeSI and HR. Perceptual scores were consistently higher than the values derived from physiological measurements, suggesting a greater subjective experience of heat strain. The PVT response times were higher on the hotter day, reflecting increased cognitive strain due to heat exposure. The study highlights the critical impact of heat stress on track workers, with statistically significant increases in physiological and cognitive strain under higher temperatures. Future research should focus on real-world applications of heat strain monitoring.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9683">https://doi.org/10.1088/1361-6579/ad9683</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <a href="/article/10.1088/1361-6579/ad9661" class="art-list-item-title event_main-link">Convolution spatial-temporal attention network for EEG emotion recognition</a> <p class="small art-list-item-meta"> Cao et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Convolution spatial-temporal attention network for EEG emotion recognition" data-link-purpose-append-open="Convolution spatial-temporal attention network for EEG emotion recognition">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9661/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, Convolution spatial-temporal attention network for EEG emotion recognition</span></a> <a href="/article/10.1088/1361-6579/ad9661/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Convolution spatial-temporal attention network for EEG emotion recognition</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>In recent years, emotion recognition using Electroencephalogram (EEG) signals has garnered significant interest due to its non-invasive nature and high temporal resolution. We introduced a groundbreaking method that bypasses traditional manual feature engineering, emphasizing data preprocessing and leveraging the topological relationships between channels to transform EEG signals from two-dimensional time sequences into three-dimensional spatio-temporal representations. Maximizing the potential of deep learning, our approach provides a data-driven and robust method for identifying emotional states. Leveraging the synergy between Convolutional Neural Network (CNN) and attention mechanisms facilitated automatic feature extraction and dynamic learning of inter-channel dependencies. Our method showcased remarkable performance in emotion recognition tasks, confirming the effectiveness of our approach, achieving average accuracy of 98.62% for arousal and 98.47% for valence, surpassing previous state-of-the-art results of 95.76% and 95.15%. Furthermore, we conducted a series of pivotal experiments that broadened the scope of emotion recognition research, exploring further possibilities in the field of emotion recognition.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9661">https://doi.org/10.1088/1361-6579/ad9661</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9662" class="art-list-item-title event_main-link">A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</a> <p class="small art-list-item-meta"> Basso et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals" data-link-purpose-append-open="A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9662/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</span></a> <a href="/article/10.1088/1361-6579/ad9662/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Objective. Pulse Decomposition Analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy. However, the physiological interpretation of the Gamma model is less effective than the Gaussian model, challenging the assessment of the clinical relevance of the outcomes. This paper aims to design an asymmetric PDA model with improved accuracy and effective physiological interpretability. Approach. We implemented a novel PDA model called the Skewed-Gaussian model and tested it on 8000 PPG pulses from the MIMIC-III Waveform Database. The performances were compared with the reference Gamma-Gaussian model. Models' accuracies were assessed using the residual sum of squares, while Bland-Altman plots were used to evaluate biases. Lastly, the sensitivity and robustness of the models to the initial values' choice were evaluated using random initial values. Main results. Our model achieved significantly higher accuracy than the reference model. The analysis with random initial values suggested that the model was less sensitive and consistently more robust. Finally, we highlighted the physiological interpretation of the model. Significance. The proposed model may help to establish a link between alterations in cardiovascular functions and variations detectable in the PPG signal, as well as opening up new avenues for PPG-based remote patient monitoring.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9662">https://doi.org/10.1088/1361-6579/ad9662</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9663" class="art-list-item-title event_main-link">openBF: an open-source finite volume 1D blood flow solver</a> <p class="small art-list-item-meta"> Benemerito et al  </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="openBF: an open-source finite volume 1D blood flow solver" data-link-purpose-append-open="openBF: an open-source finite volume 1D blood flow solver">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9663/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View accepted manuscript<span class="offscreen-hidden">, openBF: an open-source finite volume 1D blood flow solver</span></a> <a href="/article/10.1088/1361-6579/ad9663/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, openBF: an open-source finite volume 1D blood flow solver</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"> <p>Computational simulations are widely adopted in cardiovascular biomechanics because of their capability of producing physiological data otherwise impossible to measure with non-invasive modalities. &#xD;Objective&#xD;This study presents openBF, a computational library for simulating the blood dynamics in the cardiovascular system. &#xD;Approach&#xD;openBF adopts a 1-D viscoelastic representation of the arterial system, and is coupled with 0-D windkessel models at the outlets. Equations are solved by means of the finite-volume method and the code is written in Julia. We assess its predictions by performing a multiscale validation study on several domains available from the literature. &#xD;Main results&#xD;At all scales, which range from individual arteries to a population of virtual subjects, openBF's solution show excellent agreement with the solutions from existing software. For reported simulations, openBF requires low computational times. &#xD;Significance&#xD;openBF is easy to install, use, and deploy on multiple platforms and architectures, and gives accurate prediction of blood dynamics in short time-frames. It is actively maintained and available open-source on GitHub, which favours contributions from the biomechanical community.</p> </div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9663">https://doi.org/10.1088/1361-6579/ad9663</a> </div> </div> </div> </div> </div>  <p> <a href="/journal/0967-3334/acceptedmanuscripts/1">More Accepted manuscripts</a> </p>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="trending-altmetrics-tab" aria-labelledby="trending-altmetrics" hidden="hidden"> <div class="reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Trending</button> </h2> <div class="reveal-content tabpanel__content" style="display: none;">  <div class="trending-altmetric-results-list" id="https://api.altmetric.com/v1/citations/3m?num_results=5&issns=0967-3334"> <h2>Trending on Altmetric</h2> <div class="art-list"> </div> </div>  </div> </div> </div>   <div tabindex="0" role="tabpanel" id="open-access-articles-tab" aria-labelledby="open-access-articles" hidden="hidden"> <div class=" reveal-container reveal-closed reveal-enabled reveal-container--jnl-tab"> <h2 class="tabpanel__title"> <button type="button" class="reveal-trigger event_tabs-accordion" aria-expanded="false"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg>Open access</button> </h2> <div class="reveal-content tabpanel__content" style="display: none"> <p> <button data-reveal-label-alt="Close all abstracts" class="reveal-all-trigger mr-2 small" data-reveal-text="Open all abstracts" data-link-purpose-append="in this tab" data-link-purpose-append-open="in this tab"> Open all abstracts<span class="offscreen-hidden">, in this tab</span> </button> </p>  <div class="art-list"> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9798" class="art-list-item-title event_main-link">Telephone training to improve ECG quality in remote screening for atrial fibrillation</a> <p class="small art-list-item-meta"> Kethaki Prathivadi Bhayankaram <em>et al</em> 2024 <em>Physiol. Meas.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Telephone training to improve ECG quality in remote screening for atrial fibrillation" data-link-purpose-append-open="Telephone training to improve ECG quality in remote screening for atrial fibrillation">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9798/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Telephone training to improve ECG quality in remote screening for atrial fibrillation</span></a> <a href="/article/10.1088/1361-6579/ad9798/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Telephone training to improve ECG quality in remote screening for atrial fibrillation</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective:&#xD;Self-recorded, single-lead ECGs are increasingly used to diagnose arrhythmias. However, they can be of variable quality, affecting the reliability of interpretation. In this analysis of ECGs collected in atrial fibrillation screening studies, our aims were to: (i) determine the quality of ECGs when recorded unsupervised; and (ii) investigate whether telephone training improved ECG quality.&#xD;&#xD;Approach:&#xD;Data was obtained from the Screening for Atrial Fibrillation with ECG to Reduce stroke (SAFER) programme, where participants recorded four single-lead ECG traces per day for three weeks using a handheld device. ECG quality was assessed by an automated algorithm, and participants who recorded >25% poor-quality ECGs from days 4-10 of screening were identified for training to improve ECG recording technique. Training was delivered when research team capacity permitted.&#xD;&#xD;Main results:&#xD;13,741 participants recorded 1,127,264 ECGs, of which 41,288 (3.7%) were poor-quality. Most participants (51.5%) didn't record any poor-quality ECGs. 1,088 (7.9%) participants met the threshold for training. Of these, 165 participants received training and 923 didn't. The median proportion of poor-quality ECGs per participant on days 1-3 was 41.7 (27.3-50.0) % for those who received training and 33.3 (25.0-45.5) % for those who didn't. On days 11-21, the median proportions of poor-quality ECGs per participant were significantly lower (p<0.001) for those who received training, 17.8 (5.0-31.6) %, and those who didn't, 14.0 (4.8-30.2) %. Comparing these groups, the mean (95% confidence interval) reduction in proportion of poor-quality ECGs from days 1-3 to days 11-21 was 20.2 (16.8-23.5) % in those who received training and 16.0 (14.7-17.3) % in those who didn't (p=0.396). &#xD;&#xD;Significance:&#xD;Most participants achieved adequate quality ECGs. For those that didn't, ECG quality improved over time regardless of whether they received telephone training. Telephone training may therefore not be required to achieve improvements in ECG quality during screening.&#xD;</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9798">https://doi.org/10.1088/1361-6579/ad9798</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9234" class="art-list-item-title event_main-link">Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</a> <p class="small art-list-item-meta"> Marta Iovino <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115004 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices" data-link-purpose-append-open="Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9234/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</span></a> <a href="/article/10.1088/1361-6579/ad9234/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> This study evaluates the effectiveness of four machine learning algorithms in classifying physiological stress using heart rate variability (HRV) and pulse rate variability (PRV) time series, comparing an automatic feature selection based on Akaike's criterion to a physiologically-based feature selection approach. <i>Approach.</i> Linear discriminant analysis, support vector machines, <i>K</i>-nearest neighbors and random forest were applied on ten HRV and PRV indices from time, frequency and information domains, selected with the two feature selection approaches. Data were collected from 127 healthy individuals during different stress conditions (rest, postural and mental stress). <i>Main results.</i> Our results highlight that, while specific stress classification is feasible, distinguishing between postural and mental stress remains challenging. The used classifiers exhibited similar performance, with automatic Akaike Information Criterion-based feature selection proving overall better than the physiology-driven approach. Additionally, PRV-based features performed comparably to HRV-based ones, indicating their potential in outpatient monitoring using wearable devices. <i>Significance.</i> The obtained findings help to determine the most relevant HRV/PRV features for stress classification, potentially useful to highlight different physiological mechanisms involved during both challenges accompanied by a shift in the sympathovagal balance. The proposed approach may have implications for advancing stress assessment methodologies in clinical settings and real-world contexts for well-being evaluation.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9234">https://doi.org/10.1088/1361-6579/ad9234</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9683" class="art-list-item-title event_main-link">Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</a> <p class="small art-list-item-meta"> Cristina Gallego Vazquez <em>et al</em> 2024 <em>Physiol. Meas.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber" data-link-purpose-append-open="Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9683/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</span></a> <a href="/article/10.1088/1361-6579/ad9683/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Beat the heat: wearable-based study of perceived heat stress and physiological strain in Swiss track workers in a controlled climate chamber</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Increasing temperatures pose new challenges for track workers, who endure prolonged exposure to extreme heat and humidity. New methods are critically needed to assess their performance and heat tolerance, aiming to mitigate workplace accidents and long-term health consequences. This study aimed to investigate the physiological effects of heat exposure on track workers, using wearable sensors to monitor key physiological parameters under controlled environmental conditions. Nineteen track workers participated in the study, which included two experimental sessions simulating different thermal environments: a typical Swiss summer night and a hot summer day. Participants' core body temperature, heart rate (HR), and skin temperature were monitored using wearable sensors, and physiological indexes were computed. In addition, Perceptual Strain Index (PeSI) and Psychomotor Vigilance Task (PVT) response times were recorded. Statistically significant increases in physiological parameters were observed under hotter conditions. The study identified statistically significant correlations between the PeSI and the PSI and between PeSI and HR. Perceptual scores were consistently higher than the values derived from physiological measurements, suggesting a greater subjective experience of heat strain. The PVT response times were higher on the hotter day, reflecting increased cognitive strain due to heat exposure. The study highlights the critical impact of heat stress on track workers, with statistically significant increases in physiological and cognitive strain under higher temperatures. Future research should focus on real-world applications of heat strain monitoring.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9683">https://doi.org/10.1088/1361-6579/ad9683</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9662" class="art-list-item-title event_main-link">A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</a> <p class="small art-list-item-meta"> Giulio Basso <em>et al</em> 2024 <em>Physiol. Meas.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals" data-link-purpose-append-open="A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9662/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</span></a> <a href="/article/10.1088/1361-6579/ad9662/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Objective. Pulse Decomposition Analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy. However, the physiological interpretation of the Gamma model is less effective than the Gaussian model, challenging the assessment of the clinical relevance of the outcomes. This paper aims to design an asymmetric PDA model with improved accuracy and effective physiological interpretability. Approach. We implemented a novel PDA model called the Skewed-Gaussian model and tested it on 8000 PPG pulses from the MIMIC-III Waveform Database. The performances were compared with the reference Gamma-Gaussian model. Models' accuracies were assessed using the residual sum of squares, while Bland-Altman plots were used to evaluate biases. Lastly, the sensitivity and robustness of the models to the initial values' choice were evaluated using random initial values. Main results. Our model achieved significantly higher accuracy than the reference model. The analysis with random initial values suggested that the model was less sensitive and consistently more robust. Finally, we highlighted the physiological interpretation of the model. Significance. The proposed model may help to establish a link between alterations in cardiovascular functions and variations detectable in the PPG signal, as well as opening up new avenues for PPG-based remote patient monitoring.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9662">https://doi.org/10.1088/1361-6579/ad9662</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad9663" class="art-list-item-title event_main-link">openBF: an open-source finite volume 1D blood flow solver</a> <p class="small art-list-item-meta"> Ivan Benemerito <em>et al</em> 2024 <em>Physiol. Meas.</em> <b></b> </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="openBF: an open-source finite volume 1D blood flow solver" data-link-purpose-append-open="openBF: an open-source finite volume 1D blood flow solver">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad9663/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, openBF: an open-source finite volume 1D blood flow solver</span></a> <a href="/article/10.1088/1361-6579/ad9663/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, openBF: an open-source finite volume 1D blood flow solver</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p>Computational simulations are widely adopted in cardiovascular biomechanics because of their capability of producing physiological data otherwise impossible to measure with non-invasive modalities. &#xD;Objective&#xD;This study presents openBF, a computational library for simulating the blood dynamics in the cardiovascular system. &#xD;Approach&#xD;openBF adopts a 1-D viscoelastic representation of the arterial system, and is coupled with 0-D windkessel models at the outlets. Equations are solved by means of the finite-volume method and the code is written in Julia. We assess its predictions by performing a multiscale validation study on several domains available from the literature. &#xD;Main results&#xD;At all scales, which range from individual arteries to a population of virtual subjects, openBF's solution show excellent agreement with the solutions from existing software. For reported simulations, openBF requires low computational times. &#xD;Significance&#xD;openBF is easy to install, use, and deploy on multiple platforms and architectures, and gives accurate prediction of blood dynamics in short time-frames. It is actively maintained and available open-source on GitHub, which favours contributions from the biomechanical community.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad9663">https://doi.org/10.1088/1361-6579/ad9663</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad8f8f" class="art-list-item-title event_main-link">Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</a> <p class="small art-list-item-meta"> Karen McCloy <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 115002 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography" data-link-purpose-append-open="Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad8f8f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</span></a> <a href="/article/10.1088/1361-6579/ad8f8f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> Obstructive sleep apnea (OSA) is associated with deficits in vigilance. This work explored the temporal patterns of OSA-related events during sleep and vigilance levels measured by the psychomotor vigilance test (PVT) in patients undergoing polysomnography (PSG) for suspected OSA. <i>Approach.</i> The PVT was conducted prior to in-laboratory PSG for 80 patients suspected of having OSA. Three groups were formed based on PVT-RT-outcomes and participants were randomly allocated into Training (<i>n</i> = 55) and Test (<i>n</i> = 25) samples. Sleep epochs of non-rapid-eye movement (NREM) electroencephalographic (EEG) asynchrony data, and REM and NREM data for respiratory, arousal, limb movement and desaturation events were analysed. The data were segmented by sleep stage, by sleep blocks (SB) of stable Stage N2, Stage N3, mixed-stage NREM sleep (NXL), and, by Time of Night (TN) across sleep. Models associating this data with PVT groups were developed and tested. <i>Main Results.</i><b>A</b> model using NREM EEG asynchrony data segmented by SB and TN achieved 81.9% accuracy in the Test Cohort. Models based on interhemispheric asynchrony SB data and OSA data segmented by TN achieved 80.6% and 79.5% respectively. <i>Significance.</i> Novel data segmentation methods via blocks of NXL and TN have improved our understanding of the relationship between sleep, OSA and vigilance.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad8f8f">https://doi.org/10.1088/1361-6579/ad8f8f</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad7fca" class="art-list-item-title event_main-link">Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft</a> <p class="small art-list-item-meta"> Andy Adler <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 10NT01 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft" data-link-purpose-append-open="Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad7fca/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft</span></a> <a href="/article/10.1088/1361-6579/ad7fca/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. Pendelluft is the movement of air between lung regions, and electrical impedance tomography (EIT) has shown an ability to detect and monitor it. <i>Approach.</i> In this note, we propose a functional EIT measure which quantifies the reverse airflow seen in pendelluft: the <i>Fraction of Reverse Impedance Change</i> (FRIC). <i>Main</i><i>Results</i>. FRIC measures the fraction of reverse flow in each pixel waveform (as an image) or globally (as a single parameter). <i>Significance</i>. Such a measure is designed to be a more specific measure than previous approaches, to enable comparative studies of the pendelluft, and to help clarify the effect of ventilation strategies.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad7fca">https://doi.org/10.1088/1361-6579/ad7fca</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad84d4" class="art-list-item-title event_main-link">Corrigendum: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants (2024 <i>Physiol. Meas.</i> 45 055025)</a> <p class="small art-list-item-meta"> Jiaxing Qiu <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 109501 </p> <div class="art-list-item-tools small wd-abstr-upper"> <a href="/article/10.1088/1361-6579/ad84d4/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Corrigendum: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants (2024 Physiol. Meas. 45 055025)</span></a> <a href="/article/10.1088/1361-6579/ad84d4/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Corrigendum: Highly comparative time series analysis of oxygen saturation and heart rate to predict respiratory outcomes in extremely preterm infants (2024 Physiol. Meas. 45 055025)</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad84d4">https://doi.org/10.1088/1361-6579/ad84d4</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad814f" class="art-list-item-title event_main-link">An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements</a> <p class="small art-list-item-meta"> Gregorio Dotti <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 105004 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements" data-link-purpose-append-open="An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad814f/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements</span></a> <a href="/article/10.1088/1361-6579/ad814f/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective.</i> The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in clinical practice. To overcome this limitation, this study aims at presenting a toolbox to help scientists easily characterize and assess muscle activation patterns during cyclical movements. <i>Approach.</i><span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0967-3334/45/10/105004/revision2/pmeaad814fieqn1.gif" style="max-width: 100%;" alt="${\text{CIMAP}}$" align="top"></img></span><script type="math/tex">{\text{CIMAP}}</script></span></span> (Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. <i>Main results.</i> From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment of muscle activation patterns. The toolbox can be flexibly modified to comply with the necessities of the scientist. <span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0967-3334/45/10/105004/revision2/pmeaad814fieqn2.gif" style="max-width: 100%;" alt="${\text{CIMAP}}$" align="top"></img></span><script type="math/tex">{\text{CIMAP}}</script></span></span> is addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (<a href="https://github.com/Biolab-PoliTO/CIMAP">https://github.com/Biolab-PoliTO/CIMAP</a>). <i>Significance.</i><span xmlns:xlink="http://www.w3.org/1999/xlink" class="inline-eqn"><span class="tex"><span class="texImage"><img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=" data-src="https://content.cld.iop.org/journals/0967-3334/45/10/105004/revision2/pmeaad814fieqn3.gif" style="max-width: 100%;" alt="${\text{CIMAP}}$" align="top"></img></span><script type="math/tex">{\text{CIMAP}}</script></span></span> toolbox offers scientists a standardized method for analyzing muscle activation patterns during cyclical movements.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad814f">https://doi.org/10.1088/1361-6579/ad814f</a> </div> </div> </div> </div> <div class="art-list-item reveal-container reveal-closed"> <div class="art-list-item-body"> <div class="eyebrow"> <span class="offscreen-hidden">The following article is </span><span class="red">Open access</span> </div> <a href="/article/10.1088/1361-6579/ad7c05" class="art-list-item-title event_main-link">Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates</a> <p class="small art-list-item-meta"> Johannes Mader <em>et al</em> 2024 <em>Physiol. Meas.</em> <b>45</b> 095017 </p> <div class="art-list-item-tools small wd-abstr-upper"> <button type="button" class="reveal-trigger mr-2 nowrap"> <svg aria-hidden="true" class="fa-icon fa-icon--left fa-icon--flip" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path d="M137.4 374.6c12.5 12.5 32.8 12.5 45.3 0l128-128c9.2-9.2 11.9-22.9 6.9-34.9s-16.6-19.8-29.6-19.8L32 192c-12.9 0-24.6 7.8-29.6 19.8s-2.2 25.7 6.9 34.9l128 128z"/></svg><span class="reveal-trigger-label" data-reveal-text="Open abstract" data-reveal-label-alt="Close abstract" data-link-purpose-append="Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates" data-link-purpose-append-open="Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates">Open abstract</span> </button> <a href="/article/10.1088/1361-6579/ad7c05/meta" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="View article"> <span class="icon-article"></span>View article<span class="offscreen-hidden">, Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates</span></a> <a href="/article/10.1088/1361-6579/ad7c05/pdf" class="mr-2 mb-0 nowrap event_mini-link" data-event-action="PDF"><span class="icon-file-pdf"></span>PDF<span class="offscreen-hidden">, Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates</span></a> </div> <div class="reveal-content"> <div class="article-text view-text-small"><p><i>Objective</i>. This study provides an adaptive threshold algorithm for burst detection in electroencephalograms (EEG) of preterm infantes and evaluates its performance using clinical real-world EEG data. <i>Approach</i>. We developed an adaptive threshold algorithm for burst detection in EEG recordings from preterm infants. To assess its applicability in the real-world, we tested the algorithm on a dataset of 30 clinical EEG recordings which were not preselected for good quality, to ensure a real-world scenario. <i>Main results</i>. Interrater agreement was substantial at a kappa of 0.73 (0.68–0.79 inter-quantile range). The performance of the algorithm showed a similar agreement with one clinical expert of 0.73 (0.67–0.76) and a sensitivity and specificity of 0.90 (0.82–0.94) and 0.95 (0.93–0.97), respectively. <i>Significance</i>. The adaptive threshold algorithm demonstrated robust performance in detecting burst patterns in clinical EEG data from preterm infants, highlighting its practical utility. The fine-tuned algorithm achieved similar performance to human raters. The algorithm proves to be a valuable tool for automated burst detection in the EEG of preterm infants.</p></div> <div class="art-list-item-tools small wd-abstr-lower"> <a class="mr-2" href="https://doi.org/10.1088/1361-6579/ad7c05">https://doi.org/10.1088/1361-6579/ad7c05</a> </div> </div> </div> </div> </div>  <p> <a href="/nsearch?currentPage=1&terms=&nextPage=2&previousPage=-1&searchDatePeriod=anytime&journals=0967-3334&accessType=open-access&orderBy=newest&pageLength=20">More Open Access articles</a> </p> </div> </div> </div>    </div>    <aside aria-label="Main column advert"> <div id='div-gpt-ad-1562594774007-0' style='width: 728px; height: 90px; display: block;'> <script> googletag.cmd.push(function () { googletag.display('div-gpt-ad-1562594774007-0'); }); </script> </div> </aside>   </div>  </div> </main> <div class="db2 tb2"> <div class="side-and-below">  <div class="sidebar-list" id="wd-jnl-links"> <h2 class="sidebar-list__heading">Journal links</h2> <ul class="sidebar-list__list"><li><a href="http://mc04.manuscriptcentral.com/pmea-ipem" target="_blank" class="linkArrow normal link3"><strong>Submit an article</strong></a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physiological-measurement/about-physiological-measurement/">About the journal</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physiological-measurement/editorial-board/">Editorial Board</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physiological-measurement/">Author guidelines</a></li> <li><a href="https://publishingsupport.iopscience.iop.org/questions/volunteering-to-be-a-journal-reviewer">Review for this journal</li> <li><a href="https://publishingsupport.iopscience.iop.org/journals/physiological-measurement/about-physiological-measurement/#publication-charges">Publication charges</a></li> <li><a href="/0967-3334/page/Awards">Awards</a></a></li> <li><a href="https://iopscience.iop.org/journal/0967-3334/page/Journal_Collections">Journal collections</a></li> <li><a href="https://ioppublishing.org/librarians/">Pricing and ordering</a></li> <li><a href="/0967-3334/page/Contact us">Contact us</a></li></ul> </div>    <aside role="complementary" aria-label="Right sidebar adverts"> <div id='div-gpt-ad-1669279847892-0' style='min-width: 160px; 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