Xiong Peng, Qi Mingrui, Zhang Jieshuo, Liu Ming, Hou Zengguang, Wang Hongrui, Liu Xiuling
Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Feb 25;38(1):65-71. doi: 10.7507/1001-5515.202001027.
Early accurate detection of inferior myocardial infarction is an important way to reduce the mortality from inferior myocardial infarction. Regrading the existing problems in the detection of inferior myocardial infarction, complex model structures and redundant features, this paper proposed a novel inferior myocardial infarction detection algorithm. Firstly, based on the clinic pathological information, the peak and area features of QRS and ST-T wavebands as well as the slope feature of ST waveband were extracted from electrocardiogram (ECG) signals leads Ⅱ, Ⅲ and aVF. In addition, according to individual features and the dispersion between them, we applied genetic algorithm to make judgement and then input the feature with larger degree into support vector machine (SVM) to realize the accurate detection of inferior myocardial infarction. The proposed method in this paper was verified by Physikalisch-Technische Bundesanstalt (PTB) diagnostic electrocardio signal database and the accuracy rate was up to 98.33%. Conforming to the clinical diagnosis and the characteristics of specific changes in inferior myocardial infarction ECG signal, the proposed method can effectively make precise detection of inferior myocardial infarction by morphological features, and therefore is suitable to be applied in portable devices development for clinical promotion.
早期准确检测下壁心肌梗死是降低下壁心肌梗死死亡率的重要途径。针对下壁心肌梗死检测中存在的复杂模型结构和冗余特征等问题，本文提出了一种新颖的下壁心肌梗死检测算法。首先，基于临床病理信息，从心电图（ECG）信号的Ⅱ、Ⅲ和aVF导联中提取QRS和ST - T波段的峰值和面积特征以及ST波段的斜率特征。此外，根据个体特征及其之间的离散度，应用遗传算法进行判断，然后将离散度较大的特征输入支持向量机（SVM）以实现下壁心肌梗死的准确检测。本文所提方法通过德国物理技术研究院（PTB）诊断心电信号数据库进行了验证，准确率高达98.33%。该方法符合临床诊断以及下壁心肌梗死心电图信号的特定变化特征，能够通过形态学特征有效精确检测下壁心肌梗死，因此适用于临床推广的便携式设备开发。
