An implementation of motion artifacts elimination for PPG signal processing based on recursive least squares adaptive filter

Chih Chin Wu, I. Wei Chen, Wai-Chi Fang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

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.

Original languageEnglish
Title of host publication2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781509058037
DOIs
StatePublished - 23 Mar 2018
Event2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Torino, Italy
Duration: 19 Oct 201721 Oct 2017

Publication series

Name2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017 - Proceedings
Volume2018-January

Conference

Conference2017 IEEE Biomedical Circuits and Systems Conference, BioCAS 2017
CountryItaly
CityTorino
Period19/10/1721/10/17

Keywords

  • Adaptive filter
  • DC Remover
  • Motion Artifact
  • Photoplethysmography
  • Recursive Least Squares filter

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