Biomedical AI Signal Processing Systems
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
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
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
Apneal Hypopnea Index (AHI) Detection