Human Respiration Detection using Acoustic Signal

This project presents the design of an audio-based highly-accurate system for human respiration monitoring, leveraging on commodity speaker and microphone widely available in home environments. The basic idea behind the audio-based method is that when a user is close to a pair of speaker and microphone, body movement during respiration causes periodic audio signal changes, which can be extracted to obtain the respiration rate. Experimental results show that our system detects respiration with the median error lower than 0.35 breaths/min, outperforming the state-of-the-art.

This work has been reported in UbiComp 2018.

Tao Gu
Tao Gu
Distinguished Professor
IEEE Fellow
AAIA Fellow
AAIS Fellow
School of Computer Sicence, Shanghai Jiao Tong University

Address: Room 437, Building 3, SEIEE No. 800 Dongchuan Road Minhang District, Shanghai, China

Email: FirstName.LastName AT sjtu.edu.cn

My research interests include Internet of Things, Ubiquitous Computing, Mobile Computing, Embedded AI, Wireless Sensor Networks, and Big Data Analytics.