{"title":"A modified ICA framework for motion artifact removal in wrist-type photoplethysmography during exercise","authors":"S. Mushrif, A. Morales","doi":"10.1109/ISCE.2016.7797396","DOIUrl":null,"url":null,"abstract":"Removal of motion artifacts (MA) from wrist-type photoplethysmographic (PPG) signal recordings during exercise is a difficult problem, since the MA during exercise can be very strong. In this paper, a modified independent component analysis (ICA) algorithm to remove MA is proposed. The proposed algorithm relies on the negentropy scores of the linear combinations of the signal data to achieve maximum statistical independence. This algorithm was tested on PPG signals recorded during fast running. The results of the experiments reveal that this algorithm is robust to MA present in the PPG signals. The results of our algorithm are compared with the existing wavelet-decomposition method.","PeriodicalId":193736,"journal":{"name":"2016 IEEE International Symposium on Consumer Electronics (ISCE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Symposium on Consumer Electronics (ISCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCE.2016.7797396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Removal of motion artifacts (MA) from wrist-type photoplethysmographic (PPG) signal recordings during exercise is a difficult problem, since the MA during exercise can be very strong. In this paper, a modified independent component analysis (ICA) algorithm to remove MA is proposed. The proposed algorithm relies on the negentropy scores of the linear combinations of the signal data to achieve maximum statistical independence. This algorithm was tested on PPG signals recorded during fast running. The results of the experiments reveal that this algorithm is robust to MA present in the PPG signals. The results of our algorithm are compared with the existing wavelet-decomposition method.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
