关键词: J波, 支持向量机（SVM）, 核函数, 特征向量, 变步长

Abstract: Recent researches have proved that some types of J-wave syndrome are high-risk indicators of malignant arrhythmia, sudden cardiac death, and other illnesses. But the judgment of whether J-wave exists in most of the present researches relies only on electrocardiograms and clinical experience, which not only are time-consuming but can hardly avoid misdiagnoses. This paper, from the perspective of signal processing, proposes an approach for J wave auto-detection based on the variable step size support vector machine. After the optimal value of parameter [σ]of kernel function is fixed, SVM modelling is completed. Experimental results show the effectiveness of J-wave detection by this method, with the accuracy rate reaching high at 96.1%.

Key words: J wave, Support Vector Machine（SVM）, kernel function, feature vectors, variable step size