Han Yuduan, Ding Chonglong, Yang Shuo, Ge Yingfeng, Yin Jianan, Zhao Yunyue, Zhang Jinxin
Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Bioengineering (Basel). 2024 Oct 11;11(10):1012. doi: 10.3390/bioengineering11101012.
The clinical manifestations of ischemic cardiomyopathy (ICM) bear resemblance to dilated cardiomyopathy (DCM), yet their treatments and prognoses are quite different. Early differentiation between these conditions yields positive outcomes, but the gold standard (coronary angiography) is invasive. The potential use of ECG signals based on variational mode decomposition (VMD) as an alternative remains underexplored. An ECG dataset containing 87 subjects (44 DCM, 43 ICM) is pre-processed for denoising and heartbeat division. Firstly, the ECG signal is processed by empirical mode decomposition (EMD) and VMD. And then, five modes are determined by correlation analysis. Secondly, bispectral analysis is conducted on these modes, extracting corresponding bispectral and nonlinear features. Finally, the features are processed using five machine learning classification models, and a comparative assessment of their classification efficacy is facilitated. The results show that the technique proposed provides a better categorization for DCM and ICM using ECG signals compared to previous approaches, with a highest classification accuracy of 98.30%. Moreover, VMD consistently outperforms EMD under diverse conditions such as different modes, leads, and classifiers. The superiority of VMD on ECG analysis is verified.
缺血性心肌病（ICM）的临床表现与扩张型心肌病（DCM）相似，但其治疗方法和预后却大不相同。早期区分这两种病症会产生积极的结果，但金标准（冠状动脉造影）具有侵入性。基于变分模态分解（VMD）的心电图信号作为一种替代方法的潜在用途仍未得到充分探索。对一个包含87名受试者（44名DCM患者、43名ICM患者）的心电图数据集进行预处理，以进行去噪和心跳分割。首先，通过经验模态分解（EMD）和VMD对心电图信号进行处理。然后，通过相关性分析确定五个模态。其次，对这些模态进行双谱分析，提取相应的双谱和非线性特征。最后，使用五种机器学习分类模型对这些特征进行处理，并对它们的分类效果进行比较评估。结果表明，与先前的方法相比，所提出的技术使用心电图信号对DCM和ICM进行了更好的分类，最高分类准确率为98.30%。此外，在不同模态、导联和分类器等各种条件下，VMD始终优于EMD。VMD在心电图分析方面的优越性得到了验证。
