TY  - JOUR
ID  - scholars12166
KW  - Learning systems
KW  -  Accuracy; Health monitoring devices; Health monitoring system; High-speed motion; Motion artifact; Motion artifact reduction; Photoplethysmograph; Variable step-size least mean squares
KW  -  Artificial intelligence
N2  - 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.
VL  - 985
A1  - Zailan, K.A.M.
A1  - Hasan, M.H.
A1  - Witjaksono, G.
JF  - Advances in Intelligent Systems and Computing
UR  - 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
Y1  - 2019///
TI  - Variable step size least mean square optimization for motion artifact reduction: A review
SP  - 182
N1  - cited By 0; Conference of 8th Computer Science On-line Conference, CSOC 2019 ; Conference Date: 24 April 2019 Through 27 April 2019; Conference Code:225859
AV  - none
EP  - 190
PB  - Springer Verlag
SN  - 21945357
ER  -