Abstract

Mental stress is an important aspect that can, more often than not, affect the humans' performance when they attempt tasks of varying levels of complexity. Indeed, exposing the human to high levels of mental stress which he/she cannot tolerate, may affect the successful completion of the task to be accomplished. Therefore, the need for a system which can monitor the levels of the applied mental stress on human according to his/her current state is of prime importance. Hence, this work introduces a new system that can be used to automatically modify the applied mental stress according to the output of a linguistic model that employs fuzzy sets in the form of Mamdani-type fuzzy rules. This model accepts two markers which were derived based on heart rate and pupil dilation signals and predicts a performance index which is the test accuracy. Consequently, a “crisp” decision is made according to such predicted performance to alter the applied mental stress level. This system is implemented on two personal computers connected through a network; one for applying mental stress (in the form of arithmetic test), while the other is for monitoring the human mental state through the two markers and managing the mental stress levels. The results show a close match between the system's closed loop operation and the actual measurements acquired from human volunteers.

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