Optimization and validation of multiscale feature selection for EEG-based recognition of drivers’ negative emotions

Key Points

• The central aim is to develop a system for recognizing negative emotions in drivers using EEG technology.
• Optimized multiscale feature selection techniques were applied to EEG data.
• The system focused on identifying negative emotional states in drivers.
• Validation of the feature selection process was conducted to ensure effectiveness.
• The optimized system successfully recognized drivers' negative emotions.
• Findings indicate potential for enhancing traffic safety through timely interventions.