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- Title
Attention emotion recognition via ECG signals.
- Authors
Aihua Mao; Zihui Du; Dayu Lu; Jie Luo
- Abstract
Background: Physiological signal-based research has been a hot topic in affective computing. Previous works mainly focus on some strong, short-lived emotions (e.g., joy, anger), while the attention, which is a weak and long-lasting emotion, receives less attraction. In this paper, we present a study of attention recognition based on electrocardiogram (ECG) signals, which contain a wealth of information related to emotions. Methods: The ECG dataset is derived from 10 subjects and specialized for attention detection. To relieve the impact of noise of baseline wondering and power-line interference, we apply wavelet threshold denoising as preprocessing and extract rich features by pan-tompkins and wavelet decomposition algorithms. To improve the generalized ability, we tested the performance of a variety of combinations of different feature selection algorithms and classifiers. Results: Experiments show that the combination of generic algorithm and random forest achieve the highest correct classification rate (CCR) of 86.3%. Conclusion: This study indicates the feasibility and bright future of ECG-based attention research.
- Subjects
ELECTROCARDIOGRAPHY; EMOTIONS; AFFECTIVE computing; ELECTRODIAGNOSIS; HEART disease diagnosis
- Publication
Quantitative Biology, 2022, Vol 10, Issue 3, p276
- ISSN
2095-4689
- Publication type
Article
- DOI
10.15302/J-QB-021-0267