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
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference30 articles.
1. Cai, Y., Li, X., and Li, J. (2023). Emotion Recognition Using Different Sensors, Emotion Models, Methods and Datasets: A Comprehensive Review. Sensors, 23.
2. The psychological health benefits of accepting negative emotions and thoughts: Laboratory, diary, and longitudinal evidence;Ford;J. Personal. Soc. Psychol.,2018
3. Respiratory rhythm, autonomic modulation, and the spectrum of emotions: The future of emotion recognition and modulation;Jerath;Front. Psychol.,2020
4. Cardiac sympathetic-vagal activity initiates a functional brain–body response to emotional arousal;Catrambone;Proc. Natl. Acad. Sci. USA,2022
5. Autonomic nervous system development and its impact on neuropsychiatric outcome;Mulkey;Pediatr. Res.,2019
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