Adaptive Interference Cancellation for ECG Measurement based on Normalized Least Mean Square Algorithm
Article Sidebar
Main Article Content
Abstract
This paper presents an adaptive interference cancellation based on normalized least mean square (NLMS) algorithm for electrocardiogram (ECG) measurement. In general, properties of ECG signal and interference cancellation are described while ECG measuring. Basic concept of adaptive filtering based on LMS algorithm is explained shortly how to design for adaptive linear filtering for ECG interference cancellation. A set of dataset of ECG signal is used for simulation. Experimental results show that the proposed adaptive filtering based on NLMS algorithm can suppress the interference from ECG measurement in term of mean square deviation.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright @2021 Engineering Transactions
Faculty of Engineering and Technology
Mahanakorn University of Technology
References
Y.D. Lin, Y. H. Hu, “Power-line interference detection and suppression in ECG signal processing”, IEEE Trans. Biomed. Eng., vol 55, pp. 354-357, 2008.
พัลลภ พันธุปรีชารัตน์, “ความไม่เป็นอุดมคติจากการวัดสัญญาณคลื่นไฟฟ้าหัวใจผ่านส่วนต่อประสานเนื้อเยื่อ-อิเล็กโทรด”, Engineering Transactions: A Research Publication of Mahanakorn University of Technology, ปีที่ 24, ฉบับที่ 2, ก.ค. –ธ.ค. 2564.
P. Pantuprecharat, S. Masaree, P. Pawarangkoon, and C. Sawigun, “A 0.672 μW, 2 μVrms CMOS current-feedback ECG Pre-amplifier with 77 dB CMRR”, In: Proc. of IEEE Asia Pacific Conference Circuits System, Bangkok, Thailand, pp. 393–396, 2019.
B. Chen, Y. Li, X.Cao, W. Sun, W. He, “Removal of Power Line Interference From ECG Signals using Adaptive Notch Filters of Sharp Resolution”, IEEE Access, Special Section on Data-Enabled Intelligence for Digital Health, vol. 7, pp. 150667-150676, 2019.
X. Xu, Y. Liang, P. He, J. Yang, “Adaptive Motion Artifact Reduction Based on Empirical Waelet Transform and Wavelet Thresholding for the Non-Contact ECG Monitoring Systems”, Sensors, vol. 19, pp. 1-14, 2019.
A. Ren, Z. Du, J. Li, F. Hu, X. Yang, H. Abbas, “Adaptive Interference Cancellation of ECG Signals”, Sensors, vol. 17, pp. 1-15, 2017.
วิกิพีเดีย, “การบันทึกคลื่นไฟฟ้าหัวใจ”, [online] https://th.wikipedia.org/wiki/การบันทึกคลื่นไฟฟ้าหัวใจ, สืบค้นเมื่อ 21/06/2566.
S. Sitjongsataporn, “Advanced Adaptive DMT Equalisation: Algorithms and Implementation”, LAP LAMBERT Academic Publishing, 176 pages, 2011.
S. Haykin, “Adaptive Filter Theory”, Pearson, 2013.
A. Saenmuang, S. Sitjongsataporn, “Convergence and Stability Analysis of Spline Adaptive Filtering based on Adaptive Averaging Step-size Normalized Least Mean Square Algorithm”, International Journal of Intelligent Engineering and Systems (IJIES), vol. 13, no. 2, pp. 267-277, Apr. 2020.
“PhysioBank”, https://archive.physionet.org/physiobank/, สืบค้นเมื่อ 22/06/2566.
A. L. Goldberger, L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C. K. Peng, and H. E. Stanley, “PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals”, Circulation, Vol. 101, pp. e215-e220, 2000.
G. B. Moody, W. E. Muldrow, and R. G. Mark, “A Noise Stress Test For Arrhythmia Detectors”, Computers in Cardiology, Vol. 11, pp. 381-384, 1984.