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Recognition of Affective State for Austist from Stereotyped Gestures

Autists may exhibit difficulty in interaction (social and communication) with others and also stereotyped gestures. Thus, autists have difficulty to recognize and to express emotions. Human-Robot Interaction ( HRI ) researches have contributed with robotic devices able to be mediator among autist, therapists and parents. The stereotyped behaviors of these individuals are due to their defense mechanism from of their hypersensitivity. The affective state of a person can be quantify from poses and gestures. This paper proposes a system is able to infer the defense level of autists from their stereotyped gestures. This system is part of the socially assistive robot project calledHiBot . The proposed system consist of two cognitive subsystems: Hidden Markov Models (HMM ), in order to determine the stereotyped gesture, and Fuzzy Inference System ( FIS), to infer activation level of these gestures. The results of these simulations show this approach is able to infer the defense level for an task or the presence of the robot.