Driver fatigue recognition using limited amount of individual electroencephalogram.

ABSTRACT: This study aims to create a fatigue recognition system that utilizes electroencephalogram (EEG) signals to assess a driver's physiological and mental state, with the goal of minimizing the risk of road accidents by detecting driver fatigue regardless of physical cues or vehicle attributes. A fatigue state recognition system was developed using transfer learning applied to partial ensemble averaged EEG power spectral density (PSD). The study utilized layer-wise relevance propagation (LRP) analysis to identify critical cortical regions and frequency bands for effective fatigue discrimination. A total of 21 participants were included in the study, and data augmentation techniques were used to enhance the system's classification accuracy. The results indicate a significant improvement in class

SUBMITTER: Seo P 

PROVIDER: S-EPMC11704104 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature