TY - JFULL AU - Yishu Gong and Liangliang Yang and Jianyu Zhang and Zhengyu Chen and Sihong He and Xusheng Zhang and Wei Zhang PY - 2023/12/ TI - Using Speech Emotion Recognition as a Longitudinal Biomarker for Alzheimer鈥檚 Disease T2 - International Journal of Biomedical and Biological Engineering SP - 266 EP - 272 VL - 17 SN - 1307-6892 UR - https://publications.waset.org/pdf/10013336 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 203, 2023 N2 - Alzheimer鈥檚 disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer鈥檚 disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score. ER -