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摘要
The paper mainly studied the electrocardiogram wave cluster of dynamic electrocardiogram, the clustering result will find the basic wave. The study used quadratic spline wavelet to detect R wave in cardiogram, and confined the wave of an whole heart period. At same time the maximum and minimum points, related slopes were obtained as the features extraction vectors. These vectors were clustered by self-organization map (SOM) neural network. Through the experiment, the R wave detection rate was up to 99.5%, which is better than those on artificial neural network and linear filter. The basic recognition rate of 24 hours dynamic electrocardiogram, which includes 100,000 cardiogram waves, reaches 91.4%. The results reduce the cardiogram data 5-10%, which is helpful to doctor's diagnosis.
