NDLI: On the performance of AS-LMS based adaptive filter for reduction of motion artifacts from PPG signals

Content Provider	IEEE Xplore Digital Library
Author	Ram, M.R. Madhav, K.V. Krishna, E.H. Komalla, N.R. Reddy, K.A.
Copyright Year	2011
Description	Author affiliation: Dept. of E&I Engg., Kakatiya Institute of Technology & Science, Warangal, Andhra Pradesh, India (Ram, M.R.; Madhav, K.V.; Reddy, K.A.) \|\| Dept. of Anesthesiology, Govt. MGM hospitals, Warangal, Andhra Pradesh, India (Komalla, N.R.) \|\| Dept. of ECE, KU CE&T, Kakatiya University, Warangal, Andhra Pradesh, India (Krishna, E.H.)
Abstract	A Photoplethysmographic (PPG) signal is invariably corrupted with motion artifacts (MA) due to voluntary or involuntary movements of the patient. PPG is a non-invasive signal, used for the estimation of arterial blood oxygen saturation (SpO2), which helps the physician to know the hypoxic status of patient during clinical investigations. This paper presents an efficient Adaptive Step-size Least Mean Squares (AS-LMS) based adaptive filter for reducing the MA from corrupted PPG signals. The novelty of the proposed algorithm lies in the fact that a synthetic noise reference signal for adaptive filtering, representing MA noise, is generated internally from the MA corrupted PPG signal itself instead of using any additional hardware such as accelerometer or source-detector pair for acquiring noise reference signal. Convergence analysis, SNR calculations and Statistical analysis revealed that the proposed AS-LMS algorithm has a clear edge over the Time-Varying Step-size LMS (TVS-LMS) and Constant Step-size LMS (CS-LMS) based adaptive algorithms for MA reduction from PPG signals. Experimental results, for the PPG data recorded with different motion artifacts (Horizontal, Vertical and Bending motion of finger), demonstrated the efficacy of the proposed algorithm in MA reduction and thus making it best suitable for real-time pulse oximetry applications.
Starting Page	1
Ending Page	4
File Size	346603
Page Count	4
File Format	PDF
ISBN	9781424479337
ISSN	10915281
e-ISBN	9781424479351
DOI	10.1109/IMTC.2011.5944259
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-10
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise Adaptive filters Least squares approximation Filtering algorithms Fingers Estimation Blood AS-LMS Adaptive Filter PPG MA
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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