Emotional communication between human and machine using motion of joints of body

We constructed an emotion-recognition system. A method of feature extraction to discriminate emotions of human from a sensing data of human gait patterns was studied. We assume that the high dimensional biological motion data are generated by low dimensional features which components are statistically independent. The extracted feature is evaluated by a discriminated result of the given biological motion data which identified five types of categories, "Anger", "Grief", "Disgust", "Joy" and "Fear". We achieve 40% accuracy for 5-class of emotion discrimination with 3 actors' biological motion data.