Abstract:
Human emotion is a complex and psycho physiological state of mind which can be expressed as positive or negative reactions to external and internal stimuli. Typical communication channels that indicate emotions are voice and facial expressions. People who are paralyzed or have other severe movement disorders have no way of expressing their emotions thereby forming a wide communication rift between them and the outside world. Communication through eye tracking is one of the alternative ways of giving such disabled patients to interact with the outside world. This paper investigates the possibility of recognizing emotions using signal processing of Electroencephalography using discrete wavelet transform and feeding appropriate values to an adaptive neuro fuzzy inference system for classification. The system enables severely disabled as well as able users to interact with the system using eye movement in order to respond to detected emotion. The solution can be used to detect emotions of motor disabled people and provision a means of communication; also it is a learning tool for trainee neurologists. The prototype was built using Matlab successfully and it was evaluated by experts and the intended users very creditably stating it as a useful software for disabled people.