An Electrocardiogram Acquisition and Analysis System for Detection of Human Stress

Fan, Jianzhong; Li, Haihui; Zhan, Yu; Yu, Yajun

10.1109/CISP-BMEI48845.2019.8965708

2019

978-1-7281-4853-3

12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

1-6

19-21 Oct. 2019

Huaqiao, China

Institute of Electrical and Electronics Engineers Inc.

This paper introduces a system for acquiring electrocardiogram (ECG) signals of subjects using GE B30 monitor, and analyzing the data to classify the state of subjects into a mentally relaxed or stressed state. The analysis of the data is based on the heart rate variability (HRV) features extracted from ultra-short-term ECG segments. This system includes a database with 120 labeled ECG signal data and their corresponding HRV features for the training of machine learning models. The ECG signal data were recorded from 15 subjects whom are tested under both the mentally relaxed and stressed states. Test data show that the classifier of the system comes up with an accuracy of 80.56%.
© 2019 IEEE.

electrocardiogram (ECG) heart rate variability (HRV) stress detection machine learning

第一

EI

20200708158535

Biomedical engineering ; Electrocardiography ; Heart ; Image processing ; Labeled data ; Learning systems ; Machine learning

Bioengineering and Biology:461 ; Information Theory and Signal Processing:716.1

EV Compendex

Southern University of Science and Technology, Department of Electrical and Electronic Engineering, Shenzhen, China

Fan, Jianzhong,Li, Haihui,Zhan, Yu,et al. An Electrocardiogram Acquisition and Analysis System for Detection of Human Stress[C]:Institute of Electrical and Electronics Engineers Inc.,2019:1-6.