Abstract
The fatigue of miners is one of the primary factors influencing unsafe behaviors in mining. To accurately identify the fatigue status of miners, prevent coal mine accidents, and simulate the loading and unloading operations of underground mine truck drivers.Collecting electroencephalogram (EEG) and electrocardiogram (ECG) feature indicators of mine truck drivers during different work periods, using SPSS software to conduct correlation analysis on the collected fatigue feature indicators, and studying the changes in fatigue feature indicators before and after the operation of mine truck drivers. The results indicate that when the underground mine truck drivers' brainwave band entropy (β/ θ)exceeds the fatigue threshold of 60 or the HR_MEAN heart rate index is below 0.05uv, the drivers are in a state of severe fatigue. The fatigue levels of underground mine truck drivers vary during different work periods, with drivers at 13:00 experiencing the most severe fatigue. The study found that reducing the midday working hours for underground mine truck drivers can effectively decrease the occurrence of fatigue.
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