@inproceedings{527c0b3e74ca42aba95a3c2d80e50e90,
title = "An implementation of motion artifacts elimination for PPG signal processing based on recursive least squares adaptive filter",
abstract = "In Photoplethysmographic (PPG) signals analysis, the accuracy and stability are highly affected by Motion Artifacts (MAs) disturbances. In this paper, we adopt an adaptive and efficient approach based on the developed DC Remover method and Recursive Least Squares (RLS) adaptive filter for reducing MAs from PPG signals in real time. The experimental results of this work show a high correlation coefficient between Electrocardiography (ECG)-derived heart rate and PPG-derived heart rate, which is higher than 0.8504 of the R value, a high agreement by Bland-Altman analysis in the limits of agreement represent the 95% confidence interval and the standard deviation is 3.81 BPM (Beats Per Minutes). An overall PPG signal with higher signal quality is obtained. Further, the precision of heart rate calculated by PPG is improved.",
keywords = "Adaptive filter, DC Remover, Motion Artifact, Photoplethysmography, Recursive Least Squares filter",
author = "Wu, {Chih Chin} and Chen, {I. Wei} and Wai-Chi Fang",
year = "2018",
month = mar,
day = "23",
doi = "10.1109/BIOCAS.2017.8325141",
language = "English",
series = "2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--4",
booktitle = "2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings",
address = "United States",
note = "2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 ; Conference date: 19-10-2017 Through 21-10-2017",
}