ECG Multi-Emotion Recognition Based on Heart Rate Variability Signal Features Mining

Author:

Wang Ling1,Hao Jiayu1,Zhou Tie Hua1ORCID

Affiliation:

1. Department of Computer Science and Technology, School of Computer Science, Northeast Electric Power University, Jilin 132013, China

Abstract

Heart rate variability (HRV) serves as a significant physiological measure that mirrors the regulatory capacity of the cardiac autonomic nervous system. It not only indicates the extent of the autonomic nervous system’s influence on heart function but also unveils the connection between emotions and psychological disorders. Currently, in the field of emotion recognition using HRV, most methods focus on feature extraction through the comprehensive analysis of signal characteristics; however, these methods lack in-depth analysis of the local features in the HRV signal and cannot fully utilize the information of the HRV signal. Therefore, we propose the HRV Emotion Recognition (HER) method, utilizing the amplitude level quantization (ALQ) technique for feature extraction. First, we employ the emotion quantification analysis (EQA) technique to impartially assess the semantic resemblance of emotions within the domain of emotional arousal. Then, we use the ALQ method to extract rich local information features by analyzing the local information in each frequency range of the HRV signal. Finally, the extracted features are classified using a logistic regression (LR) classification algorithm, which can achieve efficient and accurate emotion recognition. According to the experiment findings, the approach surpasses existing techniques in emotion recognition accuracy, achieving an average accuracy rate of 84.3%. Therefore, the HER method proposed in this paper can effectively utilize the local features in HRV signals to achieve efficient and accurate emotion recognition. This will provide strong support for emotion research in psychology, medicine, and other fields.

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Heart Diseases Recognition Model Based on HRV Feature Extraction over 12-Lead ECG Signals;Sensors;2024-08-15

2. Advancements in Sensors and Analyses for Emotion Sensing;Sensors;2024-06-27

3. Heart Disease Prediction Model based on HRV Emotional Features Fusion;Proceedings of the 2024 8th International Conference on High Performance Compilation, Computing and Communications;2024-06-07

4. Road Rage Identification and Real-Time Monitoring: Technological Advances and Challenges;Advances in Psychology;2024

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