Prediction of Empathy Induced by Synthesized Speech using Hilbert Marginal Spectrum Analysis
- Resource Type
- Conference
- Authors
- Wang, Zhihao; Qing, Zhao; Zheng, Zeyu; Xiong, Zhiheng; Lai, Luyun; Sun, Yu
- Source
- 2023 7th International Conference on Biomedical Engineering and Applications (ICBEA) ICBEA Biomedical Engineering and Applications (ICBEA), 2023 7th International Conference on. :29-35 Apr, 2023
- Subject
- Computing and Processing
Human computer interaction
Electroencephalography
Regulation
Behavioral sciences
Spectral analysis
Biomedical engineering
EEG lateralization
Hilbert Marginal Spectrum analysis
synthesized speech
human-computer interaction
- Language
Empathy plays a pivotal role in human emotion regulation and prosocial behaviors. However, research on the neurophysiological basis of empathy is still in its early stages. The current study aimed to investigate the relationship between electroencephalography (EEG) lateralization in the frontal and parietal regions and empathy stimulated by synthesized speech in different contexts. Particularly, Hilbert marginal spectrum (HMS) analysis was employed to calculate EEG lateralization. The findings revealed that the parietal delta power asymmetry significantly predicted the empathy induced by synthesized speech in both positive context and negative contexts. Our results highlighted the potential of parietal delta power asymmetry as a biomarker for empathy induced by auditory stimuli and demonstrated the efficiency of HMS in calculating EEG lateralization.