关键词: QRS波群, ST段, 小波, 特征参数提取, 最小二乘多项式拟合

Abstract: Concerning the low accuracy and easily being interfered by noise of ECG diagnosis of ST-segment, a ST-segment detection algorithm based on least-square polynomial fitting was proposed. Firstly QRS complex was detected by dyadic spline wavelet through Mallat algorithm, then the characteristic points such as T wave, onset of QRS complex, J point, onset of T wave were detected. These characteristic points were used to judge the direction of ST-segment, and then the ST-segment was classified into line type and curve type, finally the slope of line type ST segment and concavo-convex direction of curve type ST-segment were determined through using polynomial fitting algorithm. This algorithm was certified by the simulation experiment on the signals of MIT-BIH database, and the accuracy of ST-segment shape recognition was more than 90%. The experimental results show that the algorithm reduces the noise interference of characteristic detection of ST-segment, and improves the accuracy of ST-segment detection.

Key words: QRS complex, ST-segment, wavelet, characteristic parameter extraction, least-square polynomial fitting