Abstract
The present study aimed to develop an effective method for detecting the symptoms of accumulated fatigue in order to select candidates for interview guidance as a measure to prevent health impairments due to overwork. We created a simple system by which non-experts can quickly and independently detect signs of accumulated fatigue, including subjective indices, work-related strain, task performance and physiological indices (stabilometry, autonomic nervous system indicators obtained from electrocardiogram and plethysmogram). Four university students who were busy with their undergraduate theses were asked to use the system. They used the system by themselves 16 to 21 times in a two-month period. Participants took measurements on the days when they were busy completing graduation theses and preparing for research presentations, indicating that the measurement system was easy to use. We then investigated a method for detecting signs of accumulated fatigue based on the measurement data. First, we established thresholds based on the standard deviations for each measurement. The days when a number of measurements exceeded thresholds were considered the days when signs of accumulated fatigue were detected. Symptoms were detected in all the participants on the day before or the day of graduation research oral presentation rehearsal. There was also a correspondence between days when signs were detected and events causing accumulated fatigue, indicating the validity of the present method. In order to develop a system for detecting signs of accumulated fatigue that incorporates the present method and to elicit routine use, further simplification of the measurement methods are required, and techniques for motivating users are necessary.
