Abstract
Non-contact ECG monitoring is an important method to realize long-term ECG monitoring, which is of great significance for cardiovascular diseases. However, during the monitoring process, motion artifacts will decrease the measured signal quality. This paper aims to solve the influence of motion artifacts and broaden the use scenarios of non-contact ECG monitoring. In this paper, a hybrid algorithm is proposed, which combines the stationery wavelet transform and adaptive filtering to greatly improve the adaptability of the algorithm to different kinds of motion artifacts. In order to evaluate the effectiveness of the motion artifact removal algorithm, we apply it to a variety of motion artifact interfered ECG signals collected by a self-designed non-contact ECG monitoring system. The results show that the proposed hybrid algorithm can significantly restrain the interference of motion artifacts, thus improving the signal quality. It also shows high adaptability to different types of motion artifacts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
National Center for Cardiovascular Diseases, China.: Report on cardiovascular diseases in China 2019. Beijing: Encyclopedia of China Publishing House (2020)
Harland, C.J., Clark, T.D., Prance, R.J.: Electric potential probes - new directions in the remote sensing of the human body. Meas. Sci. Technol. 13(2), 163–169 (2002)
Wang, Y., Xu, Z., Liu, S., Dai, Z., Li, J.: Noncontact ECG measuring system based on capacitive PCB electrodes. In: Ma, W., Rong, M., Yang, F., Liu, W., Wang, S., Li, G. (eds.) The Proceedings of the 9th Frontier Academic Forum of Electrical Engineering. LNEE, vol. 742, pp. 607–615. Springer, Singapore (2021). https://doi.org/10.1007/978-981-33-6606-0_55
Xu, Z., Wang, Y., Zheng, X., Ali, R.S., Li, J.: Modelling research on the mechanism of non-contact ECG measurement based on capacitive coupling. In: Ma, W., Rong, M., Yang, F., Liu, W., Wang, S., Li, G. (eds.) The Proceedings of the 9th Frontier Academic Forum of Electrical Engineering. LNEE, vol. 742, pp. 785–794. Springer, Singapore (2021). https://doi.org/10.1007/978-981-33-6606-0_72
Mason, J.W., Hancock, E.W., Gettes, L.S.: Recommendations for the standardization and interpretation of the electrocardiogram. part ii: electrocardiography diagnostic statement list. a scientific statement from the american heart association electrocardiography and arrhythmias committee, council o. Heart Rhythm 4(3), 413–419 (2007)
Pawar, T., Anantakrishnan, N.S., Chaudhuri, S., Duttagupta, S.P.: Impact of ambulation in wearable-ecg. Ann. Biomed. Eng. 36(9), 1547–1557 (2008)
Nason, G.: The stationary wavelet transform and some statistical applications. Lecture Notes in Statistics 103, Wavelet and Statistics (1995)
Mallat, S.G.: A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. 11(4) (1989)
Strasser, F., Muma, M., Zoubir, A.M.: Motion artifact removal in ECG signals using multi-resolution thresholding. Signal Processing Conference. IEEE (2012)
Goldberger, A.L., et al.: PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215-e220 [Circulation Electronic Pages. http://circ.ahajournals.org/content/101/23/e215.full. 2000 (June 13)
M. Jasim, Abdulhamed & Abd, Hamam & Abdul-Jabbar, Jassim. (2020). COMPLEXITY REDUCTION OF SLANTLET TRANSFORM STRUCTURE BASED ON THE MULTIPLIERLESS REALIZATION. https://doi.org/10.13140/RG.2.2.18094.13127
Berwal, D., Vandana, C.R., Dewan, S., Jiji, C.V., Baghini, M.S.: Motion artifact removal in ambulatory ecg signal for heart rate variability analysis. IEEE Sens. J. 19(24), 12432–12442 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Xu, Z., Wang, Y., Tian, X., Zheng, X., Li, J. (2022). Motion Artifact Removal Based on Stationary Wavelet Transform and Adaptive Filtering for Wearable ECG Monitoring. In: Yang, Q., Liang, X., Li, Y., He, J. (eds) The proceedings of the 16th Annual Conference of China Electrotechnical Society. Lecture Notes in Electrical Engineering, vol 889. Springer, Singapore. https://doi.org/10.1007/978-981-19-1528-4_69
Download citation
DOI: https://doi.org/10.1007/978-981-19-1528-4_69
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-1527-7
Online ISBN: 978-981-19-1528-4
eBook Packages: EngineeringEngineering (R0)