NDLI: A Short Study to Assess the Potential of Independent Component Analysis for Motion Artifact Separation in Wearable Pulse Oximeter Signals

Content Provider	IEEE Xplore Digital Library
Author	Jianchu Yao Warren, S.
Copyright Year	2005
Description	Author affiliation: Dept. of Tech. Syst., East Carolina Univ., Greenville, NC (Jianchu Yao)
Abstract	Motion artifact reduction and separation become critical when medical sensors are used in wearable monitoring scenarios. Previous research has demonstrated that independent component analysis (ICA) can be applied to pulse oximeter signals to separate photoplethysmographic (PPG) data from motion artifacts, ambient light, and other interference in low-motion environments. However, ICA assumes that all source signal component pairs are mutually independent. It is important to assess the statistical independence of the source components in PPG data, especially if ICA is to be applied in ambulatory monitoring environments, where motion artifacts can have a substantial effect on the quality of data received from light-based sensors. This paper addresses the statistical relationship between motion artifacts and PPG data by calculating the correlation coefficients between arterial volume variations and motion over a range of stationary to high-motion conditions. Analyses indicate that motion significantly affects arterial flow, so care must be taken when applying ICA to light-based sensor data acquired from wearable platforms
Starting Page	3585
Ending Page	3588
File Size	496227
Page Count	4
File Format	PDF
ISBN	0780387414
DOI	10.1109/IEMBS.2005.1617256
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-01-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Independent component analysis Motion analysis Biomedical monitoring Optical pulses Blood Wearable computers Optical attenuators Medical services Telemedicine Wearable sensors wearable sensors Motion artifacts independent component analysis pulse oximetry
Content Type	Text
Resource Type	Article

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