Dr. Shiwen Mao

Professor and IEEE Fellow

Auburn University, USA                                                       


RFID based Vital Sign Sensing and Its Application to Driving Fatigue Detection


With the rapid development of intelligent health sensing in the Internet of Things (IoT), vital sign monitoring (e.g., respiration) and abnormal respiration detection have attracted increasing attention. Considering the challenges and the cost of collecting labeled training data from patients with breathing related diseases, we develop the AutoTag system, an unsupervised recurrent variational autoencoder-based method for respiration rate estimation and abnormal breathing detection with off-the-shelf RFID tags and reader. Moreover, for real-time breath monitoring, a novel method is proposed to cancel the distortion on measured phase values caused by channel hopping for FCC-complaint RFID systems. We will also show how to apply RFID based sensing for an effective, low-cost driving fatigue detection system, such as detecting the nodding movements or the respiration rate of the driver, both in the highly noisy driving environment. The accurate detection performance of the proposed systems is validated by our experimental study.


Shiwen Mao received a PhD in electrical and computer engineering from Polytechnic University, Brooklyn, N.Y., in 2004. He is the Samuel Ginn Professor and Director of Wireless Engineering Research and Education Center at Auburn University, Auburn, AL. His research interests include wireless networks, multimedia communications, and smart grid. He is a recipient of several service awards from the IEEE Communications Society, several conference best paper awards, the Auburn University Creative Research & Scholarship Award in 2018, the NSF CAREER Award in 2010, and The 2004 IEEE Communications Society Leonard G. Abraham Prize in the Field of Communications Systems. He is a Fellow of the IEEE.