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Article Synopsis
  • Effective emergency responses play a critical role in preventing coal mine accidents and injuries, with this study focusing on the psychophysiological reactions during such emergencies.
  • Using virtual reality simulations, researchers analyzed emergency reactions through various statistical methods and implemented machine learning classifiers to identify key behavioral patterns like agility and panic.
  • The findings, particularly with the top-performing random forest model achieving 92% accuracy, highlight the strong connection between mental reactions to accidents and physiological changes, suggesting that these insights could improve early warning systems in the coal mining industry.
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