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REAL-TIME METHOD FOR ECG R-PEAK DETECTION COMBINING AUTOMATIC THRESHOLD AND DIFFERENTIATION
Journal of Mechanics in Medicine and Biology ( IF 0.8 ) Pub Date : 2020-11-20 , DOI: 10.1142/s0219519419500234
SI LIU 1 , ENQI ZHAN 1 , JIANBIN ZHENG 1 , LIE YU 2 , TONG XUE 3
Affiliation  

This paper proposed a novel real-time algorithm for electrocardiogram (ECG) signal analysis using the first derivative and automatic threshold to locate the R-peaks. First, the ECG signals are filtered by Butterworth low pass filter to reduce the high frequency noise. Then, the first 10[Formula: see text]s datasets of the first derivative of ECG signal are analyzed to search the maximum value. Three process thresholds are computed using this maximum value, which is used to avoid the missed and false peak detections. Thus, a threshold is automatically calculated using these searched maximum values, and divide the differentiated ECG to obtain two intersection points. Recording the time of these two intersection points, a time interval is formed for the differentiated ECG. Delaying this time interval for specific sampling periods, a new time interval is acquired for the corresponding ECG cycle. Finally, the local maximum in an ECG cycle is narrowed down in this new time interval such that the R-peak can be located. The MIT-BIH Arrhythmia Database of 48 ECG recordings is used to verify the proposed algorithm. On this dataset, the proposed algorithm yielded mean sensitivity of 99.17%, positive predictivity of 97.37% and average time error of 1.01[Formula: see text]ms.

中文翻译:

结合自动阈值和微分的心电R峰实时检测方法

本文提出了一种新颖的实时心电图 (ECG) 信号分析算法,该算法使用一阶导数和自动阈值来定位 R 峰。首先,心电信号通过巴特沃斯低通滤波器进行滤波,以降低高频噪声。然后,分析心电信号一阶导数的前10[公式:见正文]s数据集以搜索最大值。使用此最大值计算三个过程阈值,用于避免错过和错误的峰值检测。因此,使用这些搜索到的最大值自动计算阈值,并将微分后的ECG相除以获得两个交点。记录这两个交点的时间,形成一个时间间隔,用于区分心电图。将此时间间隔延迟特定采样周期,为相应的 ECG 周期获取新的时间间隔。最后,在这个新的时间间隔内缩小心电图周期中的局部最大值,从而可以定位 R 峰值。MIT-BIH 心律失常数据库 48 条心电图记录用于验证所提出的算法。在这个数据集上,所提出的算法的平均灵敏度为 99.17%,正预测率为 97.37%,平均时间误差为 1.01[公式:见正文]ms。
更新日期:2020-11-20
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