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Feature extraction of EEG and ECG for automated physiological disorder detection


Academic Report

Title: Feature extraction of EEG and ECG for automated physiological disorder detection

Reporter: Prof. ZHANG Rui (School of Mathematics, Northwestern University)

Time: November 25, 2017(Saturday) AM 9:00

Location: A#1101 room, Innovation Park Building

Contact: YANG Jie (tel: 84708351-8205)


Abstract:There has been an increasing interest in the study of the automated physiological disease detection in recent years. It could greatly reduce the burden of traditional visual inspection of medical images (e.g. EEG, ECG, MRI, X-ray etc.) by experienced physicians and deliver diagnostic services at lower cost. Commonly, it is a kind of pattern recognition problems and how to design an appropriate feature extraction method is recognized to be crucial in the successful realization. In this talk, focusing on two physiological disorders: epilepsy and atrial fibrillation (AF), we mainly introduce the automated seizure detection based on EEG and AF detection based on ECG. We first systematically introduce the background and development of seizure and AF detection methods respectively; And then, some novel EEG and ECG feature extraction methods we proposed are presented, which can be categorized into nonlinear-similarity based feature, nonlinear-interdependency based feature and nonlinear-complexity based feature; Finally, our main directions in the research of medical data analysis and neural mass modeling are given.

The brief introduction to the reporter: Zhang Rui is a young and middle-aged science and technology innovation leader in Shaanxi Province and director of medical data research center, Northwestern University. She achieved Ph.D in science and electrical and electronic engineering, respectively, in Xi'an Jiaotong University and Nanyang Technological University, Singapore. From August 2004 to January 2005, she visited the Department of Mathematics, University of Illinois, USA and from August 2013 to August 2014 she visited Harvard Medical School and Massachusetts General Hospital, USA. She mainly engages in machine learning theory and algorithms, medical data analysis and processing, neural modeling and other directions of teaching and research work. She has published over 30 academic papers at major domestic and foreign magazines and international academic conferences, presided over 5 projects of National Natural Science Foundation of China and Shaanxi Provincial Natural Science Foundation.