T. Kim, S. Kim, M. Lee, Dongil Shin, and Dongkyoo Shin (Korea)
Human computer interaction, multimodal system, artificial intelligence, and emotion recognition
This paper presents analytical methods of physiological signals which are applicable to contents. The content is driving system that composed of intelligent physics engine. A technique of driving system is proposed for intelligently embodying the user's expertise, and then evaluated by experiments with a racing car game. This study showed that effect of analysis physiological signal for artificial intelligent driving system. The intelligent driving system applies a physiological analysis module that analyzes and recognizes human physiological signal patterns. The physiological multimodal analysis system can recognize a user's emotion and concentration status by analyzing ECG(electrocardiogram) and EEG (electroencephalogram) patterns. The electroencephalogram analysis system utilizes 5 basic signal values to predict the concentration status of the user: MID_BETA, THETA, ALPHA, DELTA, and GAMMA signal. To recognize the user's electrocardiogram signal patterns, K-means-based EM algorithm was applied.
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