The present paper is to analyze the trend of sinus heart rate RR interphase sequence after a single ventricular premature beat and to compare it with the two parameters, turbulence onset (TO) and turbulence slope (TS). Based on the acquisition of sinus rhythm concussion sample, we in this paper use a piecewise linearization method to extract its linear characteristics, following which we describe shock form with natural language through cloud model. In the process of acquisition, we use the exponential smoothing method to forecast the position where QRS wave may appear to assist QRS wave detection, and use template to judge whether current cardiac is sinus rhythm. And we choose some signals from MIT-BIH Arrhythmia Database to detect whether the algorithm is effective in Matlab. The results show that our method can correctly detect the changing trend of sinus heart rate. The proposed method can achieve real-time detection of sinus rhythm shocks, which is simple and easily implemented, so that it is effective as a supplementary method.
Citation： YINWenfeng, ZHAOJie, CHENTiantian, ZHANGJunjian, ZHANGChunyou, LIDapeng, ANBaijing. Shock Shape Representation of Sinus Heart Rate Based on Cloud Model. Journal of Biomedical Engineering, 2014, 31(2): 279-282. doi: 10.7507/1001-5515.20140052 Copy
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