An ECG Segmentation Method Based on GMM and Clusterwise Regression

doi:10.1007/s42967-024-00467-x

Communications on Applied Mathematics and Computation ›› 2025, Vol. 7 ›› Issue (5): 2029-2042.doi: 10.1007/s42967-024-00467-x

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An ECG Segmentation Method Based on GMM and Clusterwise Regression

Min Li¹, Raymond Chan², Yumei Huang³, Tieyong Zeng⁴

1. School of Mathematics and Physics, Lanzhou Jiaotong University, Lanzhou, 730070, Gansu, China;
2. School of Data Science, Lingnan University, Tuen Mun, 999077, Hong Kong, China;
3. School of Mathematics and Statistics, Center for Data Science, Lanzhou University, Lanzhou, 730000, Gansu, China;
4. Faculty of Science, The Chinese University of Hong Kong, Shatin, 999077, Hong Kong, China

Received:2023-11-30 Revised:2024-04-16 Accepted:2024-05-27 Online:2025-02-22 Published:2025-02-22
Contact: Yumei Huang,E-mail:huangym@lzu.edu.cn E-mail:huangym@lzu.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (No. 11971215), the Science and Technology Project of Gansu Province of China (No. 22JR5RA391), Center for Data Science of Lanzhou University, China, and the Key Laboratory of Applied Mathematics and Complex Systems of Lanzhou University, China.

Abstract

Abstract: The electrocardiogram (ECG) segmentation needs to separate different waves from an ECG and cluster the waves simultaneously. Clusterwise regression is a useful approach that can segment and cluster the data simultaneously. In this paper, we apply the clusterwise regression method to segment the ECG. By modeling the ECG signal wave by the Gaussian mixture model (GMM) and introducing a weight function, we propose a minimization model that consists of the weighted sum of the negative log-likelihood and the total variation (TV) of the weight function. The TV of the weight function enforces the temporal consistency. A supervised algorithm is designed to solve the proposed model. Experimental results show the efficiency of the proposed method for the ECG segmentation.

Key words: Electrocardiogram (ECG), Segmentation, Fiducial point extraction, Gaussian mixture model (GMM), Clusterwise regression

Min Li, Raymond Chan, Yumei Huang, Tieyong Zeng. An ECG Segmentation Method Based on GMM and Clusterwise Regression[J]. Communications on Applied Mathematics and Computation, 2025, 7(5): 2029-2042.

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An ECG Segmentation Method Based on GMM and Clusterwise Regression

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