Emotion Recognition Using Physiological Signals
The ability to recognize emotion is one of the hallmarks of emotional intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects without much discomfort from the body surface. Film clips were used to elicit target emotions and an emotion elicitation protocol, verified to be effective in the preliminary study, was provided. Four physiological signals, electrocardiogram (ECG), skin temperature (SKT), skin conductance (SC) and respiration were selected to extract 22 features for recognition. We collected a set of data from 60 female undergraduates when experiencing the target emotion. Canonical correlation analysis was adopted as a pattern classifier, and correct-classification ratio is 85.3%. The research indicated the feasibility of user-independent emotion recognition using physiological signals. But before emotion interpretation can occur at the level of human abilities, there still remains much work to be done.
KeywordsSupport Vector Machine Emotion Recognition Physiological Signal Emotional Intelligence Canonical Correlation Analysis
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