Chronic stress evaluation using neuro-fuzzy

The purpose of this research was to evaluate chronic stress using physiological parameters. Wistar rats were exposed to sound stress for 14 days. Biosignals were acquired hourly. To develop a fuzzy inference system that can integrate physiological parameters, the parameters of the system were adjusted by the adaptive neuro-fuzzy inference system. Of the training dataset, the input dataset was the physiological parameters from the biosignals and the output dataset was the target values from the cortisol production. Physiological parameters were integrated using the fuzzy inference system, then 24-hour results were analyzed by the Cosinor method. Chronic stress was evaluated from the degree of circadian rhythm disturbance. Suppose that the degree of stress for initial rest period was 1. Then, the degree of stress after 14-day sound stress increased to 131, and increased to 1.47 after the 7-day recovery period. That is, the rat was exposed to 37%increased amount of stress by the 14-day sound and did not recover after the 7-day recovery period.