Basic experiment for switching difficulty in virtual environment

Recently, there has been considerable interest in immersive virtual workspace. This environment makes us more concentrated. Applying this environment to individual work, worker can concentrate on their works harder. Efficiency of individual work largely depends on worker's mental states. Therefore, working in accordance with worker's mental states may improve work efficiency. In this study, we focus on physiological signals such as brain wave and breathing as a method of estimating worker's mental states, which are deeply related with ones including concentration and load. So we propose task supporting method based on physiological signals in virtual environment. In this method, EEGs is used to quantify worker's mental states as an unique index of BA-Level. We also use breathing information related to worker's mental states. Worker's mental states are estimated from indexes of each physiological signals. This information is reflected to complexity and difficulty of work in virtual environment. According to the result of experiments, indexes deeply related to worker's mental states are derived from EEGs and breathing information. It was found that last 60 seconds of BA-Level and breathing frequency is related to worker's mental states. In this paper, we research the relation between difficulty of work and worker's mental states. Using this knowledge, switching method of difficulty is suggested.