Sleep accounts for about one-third of the human lifespan and plays a critical role in regulating human body’s physiological processes. Sleep disorders and their accompanying health problems affect one-in-two Canadian adults and their prevalence is increasing. In addition to its critical role in well-being and quality of life, sleep provides a unique baseline window into human body function at rest that can help characterize health and disease patterns.
In this talk, I will give an overview of current sleep technologies and their capabilities and shortcomings in monitoring sleep and health. I will then discuss how advanced sensing technologies combined with powerful data analytic methods and machine learning algorithms can be utilized to develop improved unobtrusive and portable technologies to objectively evaluate sleep, manage sleep, and monitor health status during sleep.
Zhengchen Cai, PhD candidate, will give a brief talk titled "fNIRS as a wearable/personalized technology" prior to Dr. Forouzanfar's talk.
The 1-hour seminar will be followed by a 30-minute round table discussion.
Mohamad Forouzanfar received the PhD degree in Electrical and Computer Engineering from University of Ottawa in 2014. From 2014 to 2017, he held postdoctoral positions in the School of Engineering and Applied Sciences at Harvard University and the Department of Electrical Engineering at Stanford University. From 2017 to 2020, he worked as a Research Scientist in the Center for Health Sciences at SRI International, Menlo Park, CA, USA.
He is currently an Associate Professor at École de technologie supérieure (ÉTS), Université du Québec, Montreal, QC, Canada. His area of expertise is in applied signal processing, machine learning, and instrumentation for biomedical applications.