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An Improved Method with High Anti-interference Ability for R Peak Detection in Wearable Devices
IRBM ( IF 4.8 ) Pub Date : 2020-01-24 , DOI: 10.1016/j.irbm.2020.01.002
X. Gu , J. Hu , L. Zhang , J. Ding , F. Yan

The rapid development of the wearable electrocardiogram monitoring equipment increases the requirements for R peak detection in wearable devices. An improved method called ISC algorithm is proposed with high anti-interference ability for R peak detection in wearable devices based on a simple basic algorithm called SC algorithm. The proposed method is characterized by using the updated amplitude selection threshold, updated slope comparison threshold and RR interval judgement to reduce false positives and false negatives. For data from MIT-BIH Arrhythmia Database, the positive predictivity P+ of ISC algorithm can reach 99.12%, and the sensitivity Se of ISC algorithm is more than 95%. For MIT-BIH Noise Stress Test Database, the accuracy of ISC algorithm for both sensitivity Se and positive predictivity P+ can exceed 94% under three common noise, baseline wander, muscle artifact, and electrode motion artifact, where the positive predictivity P+ of ISC algorithm is 44.46% higher than that of SC algorithm on average. For wearable devices in exercise, even under the exercise intensity of 7 km per hour, the average positive predictivity P+ of ISC algorithm is 99.32%, which is 60.93% higher than that of SC algorithm. The high anti-interference ability shows that ISC algorithm is suitable for R peak detection in wearable devices.



中文翻译:

一种高抗干扰能力的可穿戴设备R峰检测方法

可穿戴心电图监测设备的快速发展增加了对可穿戴设备中R峰检测的要求。基于一种简单的称为SC算法的基本算法,提出了一种改进的具有较高抗干扰能力的ISC算法,用于可穿戴设备中的R峰值检测。提出的方法的特征在于使用更新的幅度选择阈值,更新的斜率比较阈值和RR间隔判断来减少误报和误报。对于来自MIT-BIH心律失常数据库的数据,ISC算法的阳性预测率P +可以达到99.12%,ISC算法的灵敏度Se可以达到95%以上。对于MIT-BIH噪声压力测试数据库,ISC算法的灵敏度兼具在三种常见噪声,基线漂移,肌肉伪影和电极运动伪影下,Se和正预测性P +可以超过94%,其中ISC算法的正预测性P +平均比SC算法高44.46%。对于运动中的可穿戴设备,即使在每小时7 km的运动强度下,ISC算法的平均阳性预测率P +为99.32%,比SC算法高60.93%。较高的抗干扰能力表明,ISC算法适用于可穿戴设备中的R峰值检测。

更新日期:2020-01-24
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