Emotion recognition from physiological signals using AdaBoost

Abstract

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 AdaBoost algorithm to be served as classifier. Experimental result shows that the classifier performance was effective and steady. Emotion recognition impression was fairish and reasonable for special affective state groupings. © 2011 Springer-Verlag.