关键词: 小波Lipschitz指数, 多项式拟合, 波形分类

Abstract: Morphological change of ECG is the important diagnostic parameter to finding the malfunction of a heart.An abnormal ST segment change plays an important role in finding myocardial ischemia.Long-term ECG recording is needed because ST change is transient.It is difficult for cardiologists to find transient ST segments changes from a large amount of data and the workload is extremely heavy.The aim of this study is to classify ST according to its shape type using a polynomial approximation method and the reference STs set.The algorithm consists of feature point detection，ST change Lipschitz detection and ST shape classification.This paper applies the algorithm to the ECG data in European ST database.Through the result of the algorithm，we can know when the ST change occurs and what the ST shape type is.

Key words: wavelet Lipschitz polynomial, approximation, shape classification