University of Cambridge > > Computer Laboratory Systems Research Group Seminar > Unobtrusive Smartphone-based Mobile Health Systems: Experiences with Biological Rhythm Monitoring

Unobtrusive Smartphone-based Mobile Health Systems: Experiences with Biological Rhythm Monitoring

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A biological rhythm is any cyclic change in the level of a bodily chemical or function. Biological rhythms play a central role in maintaining our daily productivity and well-being, and can be found in almost every essential human body function, including sleep/wakefulness, respiration, walking/running, feeding, etc. Research has also linked biological rhythm disruption to serious diseases such as diabetes, obesity, or depression. In this talk, I will describe two novel smartphone systems for personalized, in-place monitoring of two important human biological rhythms, including sleep cycle and running rhythm.

Current sleep monitoring systems are often difficult to use and hence limited to sleep clinics, or invasive to users, e.g., requiring users to wear a device during sleep. We have developed iSleep—a practical smartphone App to monitor an individual’s sleep quality. iSleep uses the built-in microphone to detect the events that are closely related to sleep quality, including body movement, cough and snore, and infers quantitative measures of sleep quality. iSleep adopts a lightweight decision-tree-based algorithm to classify various events based on carefully selected acoustic features. By providing a fine-grained sleep profile that depicts details of sleep-related events, iSleep allows the user to track the sleep efficiency over time and relate irregular sleep patterns to possible causes.

Research has suggested that a proper running rhythm—the coordination between breathing and strides—helps to improve exercise efficiency and postpone fatigue. I will present iBreath – the first smartphone-based system for continuous running rhythm monitoring. iBreath is designed to be a convenient and unobtrusive exercise feedback system, and only utilizes commodity devices including smartphone and Bluetooth headset. We propose a novel approach that integrates ambient sensing based on accelerometer and microphone and a physiological model called Locomotor Respiratory Coupling (LRC) to obtain reliable running rhythm measurement.

Last, I will briefly discuss several other projects on Cyber-Physical System (CPS), including real-time volcano monitoring, aquatic monitoring using smartphone-based robotic fish, and a system platform for building smartphone-based data-intensive embedded sensing applications.

Bio: Guoliang Xing is currently an Associate Professor of Computer Science and Engineering at Michigan State University. His research interests include mobile health, Cyber-Physical Systems for sustainability, smartphone systems, and wireless networking. He received the B.S. degree from Xi’an Jiao Tong University, China, in 1998, and the M.S. and D.Sc. degrees from Washington University in St. Louis, in 2003 and 2006, respectively. His group has developed several mobile health Apps, which won two awards from the Mobile App Competition at MobiCom 2013 and 2014. He is an NSF CAREER Award recipient in 2010. He received two Best Paper Awards and five Best Paper Nominees at ICNP , IPSN, PerCom, and SECON conferences.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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