An emotional sensitive BCI in use with an expert system

Abstract

Artificial Intelligence is always striving to create a human like system. It needs to learn, talk and react to the circumstances as we humans do. To develop something like this the system has often been added some senses, like vision or hearing, so that it can react to the world around it in an intelligent way. When we humans talk, we are sending non-verbal messages that indicate our mood and how much we're involving ourselves in the conversation at hand. This is something that the system will not get from the text and therefore it needs a new parameter to help the system perceive the meaning beyond the words. This parameter can be the brainwaves that are a very good indication on the mental state of the user thus helping the system to choose the right text to guide the user to a more emotionally connected state of mind. The aim of this project is to develop a system that is more responsive to the user, a system that adapts itself to make the users feel more emotionally involved in the conversation. The adaptability feature makes the user feel that the system is responding appropriately to him like a human-to-human session. So this will create a possibility for the simulation of human endeavors. The system will try to simulate a person that can tell personal details about the user with some psychic power. This simulation has been chosen so that an emotional state of mind is more reachable. (Ol)The aim will be achieved by developing an expe1i system that will incorporate rules involving the two inputs, text and brainwaves, in order to guide the user to an emotional state. This objective is broken down into two parts. (01.1) First, use brainwaves to guide the user to an emotional state, meaning that the preferred wave is Gamma (emotional), second is Beta (concentrated), third being Alpha (awake but relaxed) and finally Theta (bored). (01.2) Secondly use keywords in conjunction with brainwaves to guide the user to an emotional state.The system was tested using 12 subjects that were divided into 3 groups. Group A was doing the session with the keywords function deactivated. Group B was doing the session with the keywords function activated. Group C, the control group, was doing the session without being effected by the brain waves and the keywords, and always showed the statements associated with the gamma wave. The data that was collected from these groups was analyzed in two comparisons. The comparison of Groups A and C was done to evaluate the success of objective 01.1 and the comparison of Groups A and B was done to evaluate the success of objective 01.2. The comparisons were done on the bases of the occurrences of the different waves for the different groups and the waves as the subjects went through the session. Testing showed that Group A did better than Group C, and Group B did better than Group A.