Emotion Recognition from Physiological Signals Using Support Vector Machine
Emotion recognition is one of the key steps towards emotional intelligence in advanced human machine interaction. This paper adopted principal component analysis (PCA) to dimensionality reduction and combined support vector machines algorithm to be used for classifier. Experimental result shows that the classifier performance was effective and useful. Emotion recognition impression was fairish and reasonable for special affective state groupings.