Abstract: This report systematically summarizes the clinical applications of new electrocardiogram (ECG) technologies in recent years, including high-frequency ECG technology, non-contact ECG technology, ECG signal processing algorithms, and deep learning models for ECG. It focuses on introducing the application achievements of high-precision ECG sensing, new ECG AI algorithms, and AI-assisted diagnosis in cardiovascular disease screening and emotional cognition, providing a new paradigm for ECG technology to move from recordability to comprehensibility and predictability.

Biography: Dr. Liu received his B.S. and Ph.D. degrees in Biomedical Engineering from Shandong University, China, in 2005 and 2010 respectively. Dr. Liu has completed the Postdoctoral trainings at Shandong University, Newcastle University in UK (2013-2014) and Emory University in USA (2015-2017). He is now the Dean of the School of Instrument Science and Engineering in Southeast University, a Professor of the State Key Laboratory of Digital Medical Engineering, and the founding Director of Wearable Heart-Sleep-Emotion Intelligent Monitoring Lab in Southeast University, leading the research works on medical big-data processing, medical device development and clinical applications. He is now the chair of Publication Committee of International Federation for Medical and Biological Engineering (IFMBE), a Council member of Chinese Society of Biomedical Engineering (CSBME), and serve as an Executive Editorial Board member for Physiological Measurement, a Deputy Editor for Medical & Biological Engineering & Computing, etc. He has published more than 300 original Journal/Conference papers, and holds more than 30 patents as an inventor. His research topics include: mHealth and intelligent monitoring, machine learning and big data processing for physiological signals, early detection and device development for cardiovascular diseases, sleep quality and emotion status monitoring.