【摘要】 本文旨在分析单次室性早搏后窦性心率RR间期的变化趋势,与震荡起始(TO)和震荡斜率(TS)参数对照。在采集窦性心律震荡的样本后,采用一种分段线性化的方法来提取其线性特征,进而通过云模型用自然语言来表示震荡形态;在采集样本的过程中,本文采用指数平滑法预测QRS波出现位置来辅助QRS波的检测,利用新的轮廓限围方法判断窦性心律。利用Matlab仿真工具,选择MIT-BIH心率失常数据库中信号进行验证,能正确检测出单次室性早搏后窦性心率的变化趋势。该算法能实现窦性心律震荡(HRT)的实时检测,并且实现简单,是一种有效的辅助检测方法。更多还原

【Abstract】 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.更多还原