Analysis of ECG signal in open heart surgery patients based on EEMD and Poincaré plot

Chuanxiang Que; Quan Liu

doi:10.1117/12.2668340

20 April 2023 Analysis of ECG signal in open heart surgery patients based on EEMD and Poincaré plot

Chuanxiang Que, Quan Liu

Author Affiliations +

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126020B (2023) https://doi.org/10.1117/12.2668340
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

Cardiovascular disease (CVD) is a serious threat for human health, its death rate outclasses other diseases. Open heart surgery, which is one of the main treatments for cardiovascular disease, is a form of invasive surgical treatment. Therefore, effective detection and analysis of cardiomotility based on body surface physiological signal have the advantage of noninvasive and nondestructive for CVD patients. Meanwhile, electrocardiograph (ECG) signal is considered a form of nonlinear, nonstationary and faint physiological signal on body surface. Heart rate variability (HRV) can be extracted and analyzed from waveform of ECG signal. In this paper, an ECG signal analyzing method based on EEMD and Poincaré plot is proposed, combined with an improved adaptive noise filtering method. First, IMF components are generated from ECG signal using EEMD. Through IMFs selection based on improved adaptive denoising method, reconstructed ECG signal is acquired. Next, RR interval sequences are extracted from original and reconstructed ECG signal respectively. Poincaré plot analysis is used on RR interval sequences and feature parameters are extracted. Finally, statistical analysis has been executed. The original data in this research were collected under open heart surgery at Far Eastern Memorial Hospital in real time. Preoperative, intraoperative and postoperative data were included. The experimental results illustrate, all features extracted from postoperative reconstruction ECG signal prove high significant difference (p<0.01) comparing to preoperation at least. The results have been discussed with physicians, and already been used for clinical auxiliary analysis. The method put forward in this paper is demonstrated feasible.

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Chuanxiang Que and Quan Liu "Analysis of ECG signal in open heart surgery patients based on EEMD and Poincaré plot", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126020B (20 April 2023); https://doi.org/10.1117/12.2668340

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KEYWORDS

Electrocardiography

Heart

Interference (communication)

Statistical analysis

Feature extraction

Signal processing

Surgery

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