Variable step size least mean square optimization for motion artifact reduction: A review
Many algorithms have been developed to reduce the motion artifact effect on Photoplethysmograph (PPG) technology and to increase the accuracy of the health monitoring device reading. It is found that existing solutions are still lacking in getting high accuracy of heart rate reading. Therefore, we p...
| Main Authors: | Zailan, K.A.M., Hasan, M.H., Witjaksono, G. |
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| Format: | Article |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.23514 / |
| Published: |
Springer Verlag
2019
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065906197&doi=10.1007%2f978-3-030-19810-7_18&partnerID=40&md5=ed1be5a986ad98c01bb92d47b1190e35 http://eprints.utp.edu.my/23514/ |
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| Summary: |
Many algorithms have been developed to reduce the motion artifact effect on Photoplethysmograph (PPG) technology and to increase the accuracy of the health monitoring device reading. It is found that existing solutions are still lacking in getting high accuracy of heart rate reading. Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). The objective of this paper is to review VSSLMS for motion artifact reduction. A total of eight manuscripts, collected from ISI, Scopus and Google Scholar indexing databases, were critically reviewed. The review revealed that VSSLMS is better than LMS in reducing the motion artifact in slow motion and high-speed motion. For future work, the VSSLMS results will be formulated with regression machine learning. © Springer Nature Switzerland AG 2019. |
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