Emotion Recognition through Physiological Signals for Human-Machine Communication
| Autor: | Alain Pruski, Choubeila Maaoui |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Support vector machine
ComputingMethodologies_PATTERNRECOGNITION medicine.diagnostic_test Computer science Speech recognition medicine Classification methods Blood volume pulse Emotion recognition Electromyography Linear discriminant analysis Human machine communication International Affective Picture System |
| Zdroj: | Cutting Edge Robotics 2010 |
| Popis: | In this paper we presented an approach to emotion recognition based on the processing of physiological signals. Physiological data was acquired in six different affective states and two pattern recognition methods have been tested: SVM method and Fisher linear discriminant. Recognition rates of about 90% were achieved for both classifiers. However, SVM classifier gives best results than Fisher discriminant using mixed features signals of different subjects. This study has shown that specific emotion pattern can be automatically recognized by a computer using physiological features. Future work on arousal, valence assessment will be used in order to identify the emotion in the valence / arousal space. We intend to use wireless sensor in order to ensure a natural and without constraints interaction between human and machine. There is also much scope to improve our system to incorporate other means of emotion recognition. Currently we are working on a facial expression system which can be integrated with physiological signal features. |
| Databáze: | OpenAIRE |
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