Toward early warning of unsafe behavior of excavator operators under time pressure: experimental evidence and EEG-based detection via RCF-IncepLite model

Key Points

• Unsafe behavior detection occurs in excavator operators under significant time pressure, highlighting operational risks.
• EEG-based metrics reveal 85% accuracy in classifying unsafe behavior during the simulated tasks.
• Experimental assessment utilized the RCF-IncepLite model to analyze real-time EEG data from operators.
• Findings indicate the potential for implementing EEG monitoring systems in high-pressure construction environments.