Performance Comparison of Variants of LMS Algorithms

Photoplethysmography (PPG) is a noninvasive method to measure heart rate which is commonly used in wearable devices. PPG measured at the wrist is corrupted with Motion Artifacts (MA) during physical activities and therefore a certain amount of signal processing is needed before estimating the heart...

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Main Authors: Welhenge, Anuradhi, Taparugssanagorn, A., Pomalaza-Raez, C.
Format: Journal Article
Published: 2019
Online Access:http://hdl.handle.net/20.500.11937/90308
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author Welhenge, Anuradhi
Taparugssanagorn, A.
Pomalaza-Raez, C.
author_facet Welhenge, Anuradhi
Taparugssanagorn, A.
Pomalaza-Raez, C.
author_sort Welhenge, Anuradhi
building Curtin Institutional Repository
collection Online Access
description Photoplethysmography (PPG) is a noninvasive method to measure heart rate which is commonly used in wearable devices. PPG measured at the wrist is corrupted with Motion Artifacts (MA) during physical activities and therefore a certain amount of signal processing is needed before estimating the heart rate. There are several proposed methods to remove MAs from a PPG, such as independent component analysis, sparse spectrum based methods, and Singular Value Decomposition (SVD). These methods have a high complexity compared to the Least Mean Square (LMS) adaptive later technique with acceleration data as the reference signal. In this paper, the performances of several types of LMS liters are computed and compared with the performance of the SVD method. The results show that the general LMS algorithm and the normalized LMS algorithm perform better than the other variants of LMS algorithm and that the general LMS algorithm performs better than the SVD. An autoregressive integrated moving average (ARIMA) model of the PPG signal has also been estimated for future applications of this signal.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-903082023-02-28T04:33:06Z Performance Comparison of Variants of LMS Algorithms Welhenge, Anuradhi Taparugssanagorn, A. Pomalaza-Raez, C. Photoplethysmography (PPG) is a noninvasive method to measure heart rate which is commonly used in wearable devices. PPG measured at the wrist is corrupted with Motion Artifacts (MA) during physical activities and therefore a certain amount of signal processing is needed before estimating the heart rate. There are several proposed methods to remove MAs from a PPG, such as independent component analysis, sparse spectrum based methods, and Singular Value Decomposition (SVD). These methods have a high complexity compared to the Least Mean Square (LMS) adaptive later technique with acceleration data as the reference signal. In this paper, the performances of several types of LMS liters are computed and compared with the performance of the SVD method. The results show that the general LMS algorithm and the normalized LMS algorithm perform better than the other variants of LMS algorithm and that the general LMS algorithm performs better than the SVD. An autoregressive integrated moving average (ARIMA) model of the PPG signal has also been estimated for future applications of this signal. 2019 Journal Article http://hdl.handle.net/20.500.11937/90308 10.26717/BJSTR.2019.14.002485 http://creativecommons.org/licenses/by/4.0/ fulltext
spellingShingle Welhenge, Anuradhi
Taparugssanagorn, A.
Pomalaza-Raez, C.
Performance Comparison of Variants of LMS Algorithms
title Performance Comparison of Variants of LMS Algorithms
title_full Performance Comparison of Variants of LMS Algorithms
title_fullStr Performance Comparison of Variants of LMS Algorithms
title_full_unstemmed Performance Comparison of Variants of LMS Algorithms
title_short Performance Comparison of Variants of LMS Algorithms
title_sort performance comparison of variants of lms algorithms
url http://hdl.handle.net/20.500.11937/90308