地点： 经管楼 312室
题目： A Deep Learning-Based Method for Sleep Stage Classification Using Physiological Signal
报告人： Chao-Hsien Chu
Professor of Information Sciences and Technology (IST)
Pennsylvania State University, USA.
A huge number of people suffers from different types of sleep disorders, such as insomnia, narcolepsy, and apnea. A correct classification of their sleep stage is a prerequisite and essential step to effectively diagnose and treat their sleep disorders. Sleep stages are often scored by experts through manually inspecting the patients’ polysomnography (PSG), which is usually needed to be collected in hospitals. It is very laborious for experts and discommodious for patients to go through the process. Accordingly, current studies focused on automatically identifying the sleep stages and nearly all of them need to use hand-crafted features to achieve decent performance. However, the extraction and selection of these features are time-consuming and require domain knowledge. In this study, we adopt and present a deep learning approach for automatic sleep stage classification using raw physiological signal. Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) of popular deep learning models are employed to automatically learn features from raw physiological signals and identify the sleep stages. Our experiments showed that the proposed deep learning-based method has better performance than previous work. Hence, it can be a promising tool for patients and doctors to monitor the sleep condition and diagnose the sleep disorder timely.
Dr. Chao-Hsien Chu is a Professor of Information Sciences and Technology (IST) at the Pennsylvania State University, University Park, PA, USA. He has served in several critical leadership position at Penn State’s IST, including as Senior Academic Director of the IST Online Program, Co-director of the Center of Cyber Security, Information Privacy and Trust, and Director of the Smart Sensing Lab. He was a visiting Professor and Associate Dean at the School of Information Systems, Singapore Management University, Singapore from 2012-2014.
Chu received his Ph.D. in Business Administration (Management Sciences & Information Systems) from Penn State. He has taught at the College of Business of Iowa State University and at the Zicklin School of Business, Baruch College, City University of New York. Chu’s current research focuses on (1) Smart Sensing/Internet of Things, especially in complex event processing (CEP), analytics, and security & privacy, and their applications in healthcare, supply chains, and environmental monitoring; (2) Cyber Security and Privacy, especially in mobile security, privacy preserving and risk management; (3) Analytics and Informatics, especially for healthcare informatics and fraud detection; and (4) Operations and Technology Innovation including lean thinking, process reengineering, and supply chain integration and management.
Dr. Chu have published more than 190 papers, many of them are in top-tier journals and major conference proceedings such as INFORMS Journal on Computing, Decision Sciences, Journal of Operations Management, IIE Transactions, European Journal of Information Systems, European Journal of Operational Research, Decision Support Systems, International Journal of Production Research, IEEE Sensors Journal, IEEE Internet of Things (IoT) Journal, IEEE Transactions on Dependable and Secure Computing, IEEE Transactions on Evolutionary Computation, IEEE Security & Privacy, International Conf. of the IEEE Engineering in Medicine and Biology Society (EMBS), IEEE Sensors Conf., ACM Conf. on Computer and Communication Security (CCS), and other high-quality of outlets. Five of his papers received the best paper award and one of the dissertations he supervised received honorable mentioned from Decision Sciences Institute.