Biomedical AI Signal Processing Systems

Sleep Apnea Syndrome Signal Processing and Artificial Intelligence Homecare System:

Sleep apnea syndrome (SAS, 睡眠呼吸中止症) is a popular but easily-ignored disease for modern people. Traditional polysomnography (PSG) examination is labor-intensive SAS diagnosis method and the wearing devices of the PSG are complicated and uncomfortable. This research project cooperates with Prof. Po-Chiun Huang and Prof. Hsi-Pin Ma of NTHU EE, Doctor Yu-Lun Lo of Linkou Chang Gung Memorial Hospital, and Prof. Hau-Tieng Wu of Duke University, USA. This research develops a wearable 3D accelerometer/SpO2/ECG device as IoT Sensors and designs sleep-apnea event detection/classification/analysis algorithms on the Cloud AI computing Server for Tele-homecare monitoring systems.

Research topics : Fused detection of sleep apnea by 3D acceleromenter and ECG signals, Sensor IoT and Cloud AI analysis for SAS homecar systems.

3D accelerometer sensing system
Sleep Apnea detection algorithm