Abstract
BCI (Brain-computer Interface) has been attracting attention as an interface to connect the brain to external devices. However, it is essential to establish methods to recognize the brain state accurately in order to implement BCI, and a number of challenges still remain. Here, we suggest a novel BCI system that accurately recognizes and isolates emotions like delight, anger, sorrow, and pleasure using an Emotion Fractal Analysis Method (EFAM), which can quantify emotions based on data obtained by electroencephalography, and control an electric wheelchair using the information. With this method, a high average rate of recognizing emotions (delight, anger, sorrow, and pleasure) of 55–60% and markedly high rate of isolating them of over 97% can be achieved. We developed the BCI circuit to control an electric wheelchair based on data on emotions obtained in realtime by EFAM. Using this circuit, the speed of an electric wheelchair can be adjusted by the intensity of emotions.
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