Activity Recognition in Wearable ECG Monitoring Aided by Accelerometer Data

被引：18

作者：

Liu, Juzheng ^{[1
]}

Chen, Jing ^{[2
]}

Jiang, Hanjun ^{[2
]}

Jia, Wen ^{[3
]}

Lin, Qingliang ^{[3
]}

Wang, Zhihua ^{[2
,3
]}

机构：

[1] Tsinghua Univ, Dept Phys, Beijing, Peoples R China

[2] Tsinghua Univ, Inst Microelect, Tsinghua Natl Lab Info Sci & Tech, Beijing, Peoples R China

[3] Res Inst Tsinghua Shenzhen, Shenzhen Engn Lab Wireless Healthcare IC Tech, Shenzhen, Guangdong, Peoples R China

来源：

2018 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS) | 2018年

关键词：

wearable device; electrocardiogram (ECG); activity recognition; accelerometer;

D O I：

10.1109/ISCAS.2018.8351076

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A wearable ECG monitoring device with accelerometer aided activity recognition is proposed in this work. A 3-axis accelerometer is integrated in the Band-Aid alike wearable device which will be stuck to the user's chest. The Lead V2 ECG signal and the chest acceleration data are recorded synchronously. An activity recognition algorithm is proposed to identify certain types of daily activities, including coughing, walking, standing, sitting, squatting or lying based on the chest acceleration data. The recognition result can be further used to correlate the recorded ECG signal to the user's activity. Experiments on 13 volunteers with age of 5 to 68 show that the proposed algorithm have an overall accuracy of 96.92%. The recognition result can be further used to correlate the recorded ECG signal to the user's activities.

引用

页数：4

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