The mapping relationship between PERCLOS and work fatigue: a correlation verification experiment based on radial basis function neural network

Abstract

Work fatigue is one of the main causes. The main purpose of this article is to discuss the mapping relationship between PERCLOS and human work fatigue through confirmatory experiments, as well as the availability of com-pound eye movement parameter analysis based on the random forest neural network model for fatigue detection in specific tasks. A total of 16 subjects were recruited in this experiment. The performance of the subjects was obtained through the improved measurement of the number of write-off symbols, and the response of the subjects was obtained by the two-point click reaction time measurement method. The obtained performance and response time data were used to reflect the fatigue degree of the subjects and use Diskablis eye tracker to record the eye movement parameters of the subjects. In the end, it was found that PERCLOS and two-point click response time had a correlation with fatigue status, and there was a more potential relationship between other performance parameters and fatigue. The compound eye movement parameter analysis method based on the random forest neural network model also has high usability in fatigue detection.