Abstract
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.
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Caitlin, M.: The Apple Watch 4 is giving some cardiologists pause. https://www.tomsguide.com/us/apple-watch-series-4-ekg-sensor,news-28081.html. Accessed 28 Sept 2018
Han, H., Kim, J.: Artifacts in wearable photoplethysmographs during daily life motions and their reduction with least mean square based active noise cancellation method. Comput. Biol. Med. 42(4), 387–393 (2012)
Sun, B., Zhang, Z.: Photoplethysmography-based heart rate monitoring using asymmetric least squares spectrum subtraction and bayesian decision theory. IEEE Sens. J. 15(12), 7161–7168 (2015)
Ye, Y., He, W., Cheng, Y., Huang, W., Zhang, Z.: A robust random forest-based approach for heart rate monitoring using photoplethysmography signal contaminated by intense motion artifacts. Sensors 17(2), 385 (2017)
Sawh, M.: ECG explained: why the HR tech from the Apple Watch Series 4 is a big deal. https://www.wareable.com/health-and-wellbeing/ecg-heart-rate-monitor-watch-guide-6508. Accessed 28 Sept 2018
Redesigned Apple Watch Series 4 revolutionizes communication, fitness and health. https://www.apple.com/newsroom/2018/09/redesigned-apple-watch-series-4-revolutionizes-communication-fitness-and-health/. Accessed 24 Sept 2018
Zhang, G., Wu, T., Wan, Z., Song, Z., Yu, M., Wang, D., Li, L., Chen, F., Xu, X.: A method to differentiate between ventricular fibrillation and asystole during chest compressions using artifact-corrupted ECG alone. Comput. Methods Programs Biomed. 141, 111–117 (2017)
Wijshoff, R., Mischi, M., Aarts, R.: Reduction of periodic motion artifacts in photoplethysmography. IEEE Trans. Biomed. Eng. 64(1), 196–207 (2017)
Peng, F., Zhang, Z., Gou, X., Liu, H., Wang, W.: Motion artifact removal from photoplethysmographic signals by combining temporally constrained independent component analysis and adaptive filter. BioMed. Eng. OnLine 13(1), 50 (2014)
Warren, K., Harvey, J., Chon, K., Mendelson, Y.: Improving pulse rate measurements during random motion using a wearable multichannel reflectance photoplethysmograph. Sensors 16(3), 342 (2016)
Tautan, A.-M., Young, A., Wentink, E., Wieringa, F.: Characterization and reduction of motion artifacts in photoplethysmographic signals from a wrist-worn device. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2015)
Yousefi, R., Nourani, M., Ostadabbas, S., Panahi, I.: A motion-tolerant adaptive algorithm for wearable photoplethysmographic biosensors. IEEE J. Biomed. Health Inform. 18(2), 670–681 (2014)
Lo, F.P.-W., Meng, M.Q.-H.: Double sensor complementary placement method to reduce motion artifacts in PPG using fast independent component analysis. In: 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2016)
Majumder, S., Mondal, T., Deen, M.: Wearable sensors for remote health monitoring. Sensors 17(12), 130 (2017)
Khan, Y., Ostfeld, A.E., Lochner, C.M., Pierre, A., Arias, A.C.: Monitoring of vital signs with flexible and wearable medical devices. Adv. Mater. 28(22), 4373–4395 (2016)
Clarke, G.W.J., Chan, A.D.C., Adler, A.: Effects of motion artifact on the blood oxygen saturation estimate in pulse oximetry. In: 2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA) (2014)
Chan, K., Zhang, Y.: Adaptive reduction of motion artifact from photoplethysmographic recordings using a variable step-size LMS filter. In: Proceedings of IEEE Sensors (2002)
Li, H., Tong, N., Liu, N., Jiang, J.: A new variable-step-size LMS adaptive filtering algorithm. In: 2008 9th International Conference on Signal Processing (2008)
Schack, T., Sledz, C., Muma, M., Zoubir A.M.: A new method for heart rate monitoring during physical exercise using photoplethysmographic signals. In: 2015 23rd European Signal Processing Conference (EUSIPCO) (2015)
Bismor, D., Czyz, K., Ogonowski, Z.: Review and comparison of variable step-size LMS algorithms. Int. J. Acoust. Vibr. 21(1), 24–39 (2016)
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Zailan, K.A.M., Hasan, M.H., Witjaksono, G. (2019). Variable Step Size Least Mean Square Optimization for Motion Artifact Reduction: A Review. In: Silhavy, R. (eds) Artificial Intelligence Methods in Intelligent Algorithms. CSOC 2019. Advances in Intelligent Systems and Computing, vol 985. Springer, Cham. https://doi.org/10.1007/978-3-030-19810-7_18
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DOI: https://doi.org/10.1007/978-3-030-19810-7_18
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