Motion sensor aided motion artifact recognition and removal method for ECG

CHEN Jing; JIANG Han-jun; XU Nai-hao; WANG Zhi-hua

doi:10.13873/J.1000-9787(2016)01-0049-03

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Motion sensor aided motion artifact recognition and removal method for ECG

更新时间：2025-09-11

- Motion sensor aided motion artifact recognition and removal method for ECG
- Vol. 35, Issue 1, Pages: 49-51+55(2016)
- 作者机构：
  
  清华大学微电子与纳电子学系
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)01-0049-03
  CLC： TP391.41
- Published：2016
- 稿件说明：
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[1]陈静,姜汉钧,徐乃昊,王志华.运动传感器辅助的心电运动伪迹识别与消除方法[J].传感器与微系统,2016,35(01):49-51+55.

CHEN Jing, JIANG Han-jun, XU Nai-hao, et al. Motion sensor aided motion artifact recognition and removal method for ECG[J]. 2016, 35(1): 49-51+55.
[1]陈静,姜汉钧,徐乃昊,王志华.运动传感器辅助的心电运动伪迹识别与消除方法[J].传感器与微系统,2016,35(01):49-51+55. DOI： 10.13873/J.1000-9787(2016)01-0049-03.

CHEN Jing, JIANG Han-jun, XU Nai-hao, et al. Motion sensor aided motion artifact recognition and removal method for ECG[J]. 2016, 35(1): 49-51+55. DOI： 10.13873/J.1000-9787(2016)01-0049-03.

摘要

运动伪迹是动态心电监护的主要干扰

严重影响临床诊断的误诊率和漏诊率。为了改善动态心电信号质量

设计了一种运动传感器辅助的动态心电监护设备

采集V2导联心电信号

通过腹部运动传感器数据识别易引起心电运动伪迹的日常活动

标记运动伪迹位置

引入PQRST波特征点检测、自适应滤波算法消除运动伪迹。实际佩戴测试结果表明:此法可有效识别咳嗽、蹲、坐等日常运动

并有效消除此类运动产生的心电运动伪迹。

Abstract

Motion artifact is the main interference of dynamic ECG monitoring and will affect fault diagnosis rate and missed diagnosis rate. In order to improve dynamic ECC signal quality

a motion sensor aided dynamic ECG monitoring system is designed

this system collects V2 lead ECG signal

through abdominal motion sensor data

identify patient ’s daily activity which easy to cause motion artifact of ECG motion

label position of motion artifact

introduce PQRST wave feature points detection and adaptive filtering algorithm to remove the motion artifact. The effectiveness of this algorithm is verified by actual ECG signals

daily activities such as coughing

squatting and sitting can be recognized and ECG motion artifact caused by such activities can be removed by this method effectively.

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references

便携式心电采集系统及实时分析算法研究 [D]. 周雅琪. 浙江大学 2014

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