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Novel tailoring algorithm for abrupt motion artifact removal in photoplethysmogram signals
Limeng Pu,Pedro J. Chacon,Hsiao-Chun Wu,최진우 대한의용생체공학회 2017 Biomedical Engineering Letters (BMEL) Vol.7 No.4
Photoplethysmogram (PPG) signals are widelyused for wearable electronic devices nowadays. The PPGsignal is extremely sensitive to the motion artifacts (MAs)caused by the subject’s movement. The detection andremoval of such MAs remains a difficult problem. Due tothe complicated MA signal waveforms, none of the existingtechniques can lead to satisfactory results. In this paper,a new framework to identify and tailor the abrupt MAs inPPG is proposed, which consists of feature extraction,change-point detection, and MA removal. In order toachieve the optimal performance, a data-dependent framesizedetermination mechanism is employed. Experimentsfor the heart-beat-rate-measurement application have beenconducted to demonstrate the effectiveness of our proposedmethod, by a correct detection rate of MAs at 98% and theaverage heart-beat-rate tracking accuracy above 97%. Onthe other hand, this new framework maintains the originalsignal temporal structure unlike the spectrum-basedapproach, and it can be further applied for the calculationof blood oxygen level (SpO2).