PAIR Conference 2023

Prof. Changyuan YU received his Ph.D. in Electrical Engineering from the Univ. of Southern California, USA in 2005. He was a visiting researcher at NEC Labs America in Princeton, USA in 2005. He then joined National Univ. of Singapore (NUS) in 12/2005, where he served as the founding leader of Photonic System Research Group in Dept. of Electrical and Computer Engineering till 12/2015. He was also a joint senior scientist with A*STAR Institute for Infocomm Research (I2R) in this period. And he was a visiting professor with Univ. of Melbourne, Australia in 2007. In 12/2015, he joined The Hong Kong Polytechnic Univ., where he is now a full professor in Dept. of Electronic and Information Engineering, while he also continues as an adjunct faculty member of NUS. His research focuses on photonic devices, optical fiber communication and sensor systems, and biomedical instruments. He has been the PI/co-PI/co-I of 50+ research projects with 10 million+ US dollars fund, and supervised 20+ postdocs and 40+ PhD students. He has authored/co-authored 6 book chapters and 600+ journal/conference papers (100+ keynote/invited, including OFC in USA). He served in organizing or technical program committees for 100+ international conferences, and Telecommunications Standards Advisory Committee for Singapore government. His group won 10 best paper awards in conferences and National Championship in China Innovation and Entrepreneurship Competition in 2014. He is an Optica/OSA fellow.

Topic: "Non-wearable non-invasive smart health monitoring system based on optical fiber interferometer with machine learning"

^Abstract

With the population ageing globally, “elderly health and care” becomes a critical issue in Hong Kong and worldwide. Vital signs (including breath and heartbeat) monitoring is a key tool in elderly healthcare. Current monitors need invasive electronic sensors attached to user’s body, which is inconvenient and uncomfortable for elderly. We review our research on smart health monitoring system based on optical fiber interferometer with machine learning. Users simply lie/sleep on a sensor mat embedded with optical fiber interferometer. Breath and heartbeat will introduce slight strain changes on the mat and affect the light propagating within the fiber. Breathing and heartbeat waveforms can be achieved by analyzing the output light with machine learning. The system can collect user’s signals continuously and remotely to provide big data for health analysis. It helps to provide good care of the users (especially elderly) in hospitals, nursing homes, and their own homes. Our technique is non-invasive, highly sensitive, and immune to electromagnetic interference.