Search results for: Luay Fraiwan

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Fraiwan</title> <meta name="description" content="Search results for: Luay Fraiwan"> <meta name="keywords" content="Luay Fraiwan"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Luay Fraiwan"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 2</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Luay Fraiwan</h1> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Extraction of Fetal Heart Rate and Fetal Heart Rate Variability from Mother's ECG Signal</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Khaldon%20Lweesy">Khaldon Lweesy</a>, <a href="https://publications.waset.org/search?q=Luay%20Fraiwan"> Luay Fraiwan</a>, <a href="https://publications.waset.org/search?q=Christoph%20Maier"> Christoph Maier</a>, <a href="https://publications.waset.org/search?q=Hartmut%20Dickhaus"> Hartmut Dickhaus</a> </p> <p class="card-text"><strong>Abstract:</strong></p> <p>This paper describes a new method for extracting the fetal heart rate (fHR) and the fetal heart rate variability (fHRV) signal non-invasively using abdominal maternal electrocardiogram (mECG) recordings. The extraction is based on the fundamental frequency (Fourier-s) theorem. The fundamental frequency of the mother-s electrocardiogram signal (fo-m) is calculated directly from the abdominal signal. The heart rate of the fetus is usually higher than that of the mother; as a result, the fundamental frequency of the fetal-s electrocardiogram signal (fo-f) is higher than that of the mother-s (fo-f > fo-m). Notch filters to suppress mother-s higher harmonics were designed; then a bandpass filter to target fo-f and reject fo-m is implemented. Although the bandpass filter will pass some other frequencies (harmonics), we have shown in this study that those harmonics are actually carried on fo-f, and thus have no impact on the evaluation of the beat-to-beat changes (RR intervals). The oscillations of the time-domain extracted signal represent the RR intervals. We have also shown in this study that zero-to-zero evaluation of the periods is more accurate than the peak-to-peak evaluation. This method is evaluated both on simulated signals and on different abdominal recordings obtained at different gestational ages.</p> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Aabdominal%20ECG" title="Aabdominal ECG">Aabdominal ECG</a>, <a href="https://publications.waset.org/search?q=fetal%20heart%20rate%20variability" title=" fetal heart rate variability"> fetal heart rate variability</a>, <a href="https://publications.waset.org/search?q=frequency%20harmonics" title=" frequency harmonics"> frequency harmonics</a>, <a href="https://publications.waset.org/search?q=fundamental%20frequency." title=" fundamental frequency."> fundamental frequency.</a> </p> <a href="https://publications.waset.org/14006/extraction-of-fetal-heart-rate-and-fetal-heart-rate-variability-from-mothers-ecg-signal" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/14006/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/14006/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/14006/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/14006/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/14006/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/14006/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/14006/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/14006/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/14006/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/14006/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/14006.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">2673</span> </span> </div> </div> <div class="card publication-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/search?q=Luay%20A.%20Fraiwan">Luay A. Fraiwan</a>, <a href="https://publications.waset.org/search?q=Natheer%20Y.%20Khaswaneh"> Natheer Y. Khaswaneh</a>, <a href="https://publications.waset.org/search?q=Khaldon%20Y.%20Lweesy"> Khaldon Y. Lweesy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Features%20selection" title="Features selection">Features selection</a>, <a href="https://publications.waset.org/search?q=regression%20trees" title=" regression trees"> regression trees</a>, <a href="https://publications.waset.org/search?q=sleep%20stagescoring" title=" sleep stagescoring"> sleep stagescoring</a>, <a href="https://publications.waset.org/search?q=wavelet%20packets." title=" wavelet packets."> wavelet packets.</a> </p> <a href="https://publications.waset.org/9194/automatic-sleep-stage-scoring-with-wavelet-packets-based-on-single-eeg-recording" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/9194/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a 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Search results for: Luay Fraiwan