안녕하세요, EIRIC (이릭, 전자정보연구정보센터) 입니다.
2022년 11월 29일 (화) 오후 2시 EIRIC 세미나 소식입니다.
EIRIC 세미나는 연구자들간의 정보 공유 및 상호 토론 등을 위한 무료 온라인 세미나입니다.
관련 연구자분들의 연구활동에 도움이 되시기를 기대하며, 관심있는 분들의 많은 참가 바랍니다.
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고정길 교수 | 연세대학교 글로벌융합공학부
2022년 11월 29일 (화) 오후 2시 참가신청 This talk will discuss two mobile/embedded systems that involve the analysis of time series data (one numerical and the other image) using deep learning models. The first part of the talk presents HeartQuake, a low cost, accurate, non-intrusive, geophone-based sensing system for extracting accurate electrocardiogram (ECG) patterns using heartbeat vibrations that penetrate through a bed mattress. In HeartQuake, cardiac activity-originated vibration patterns are captured on a geophone and sent to a server, where the data is filtered to remove the sensor’s internal noise and passed on to a bidirectional long short term memory (Bi-LSTM) deep learning model for ECG waveform estimation. Our extensive experimental results with baseline dataset collected from 21 study participants and a longitudinal dataset from 15 study participants suggest that HeartQuake, even when using a general non-personalized model, can detect all five ECG peaks (e.g., P, Q, R, S, T) with an average error of as low as 13 msec when participants are stationary on the bed. Furthermore, clinically used ECG metrics such as RR interval and QRS segment width can be estimated with errors as low as 3 msec and 10 msec, respectively. When additional noise factors are present (e.g., external vibration and various sleeping habits), the estimation error increases, but can be mitigated by using a personalized model. Finally, a qualitative study with 11 physicians on the clinically perceived quality of HeartQuake-generated ECG signals suggests that HeartQuake can effectively serve as a screening tool for detecting and diagnosing abnormal cardiovascular conditions... 자세히보기 |