Biomedical AI Signal Processing Systems

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                     

        

         

                              Apneal Hypopnea Index (AHI) Detection