Nonlinear EEG Analysis for Distinguishing Mind Wandering and Focused Attention: A Machine Learning Approach
bioRxiv – October 18, 2024
Source: medRxiv/bioRxiv/arXiv
Summary
Did you know that our brains can be analyzed to tell if we're daydreaming or focused? By examining EEG data, researchers successfully distinguished between mind wandering and focused attention using advanced machine learning. They achieved an impressive 75% accuracy, highlighting the potential of brain activity analysis in understanding our mental states.
Abstract
This study uses nonlinear analysis techniques to distinguish between mind wandering (MW) and focused attention (FA) states using EEG data. EEG recordings from 21 sessions were segmented into intervals of 2, 3, 5, 6, 10, and 15 seconds, and seven nonlinear features were extracted to capture the brain’s dynamic complexity. Machine learning models, including gradient boosting trees, were applied to classify MW and FA states, with the highest accuracy of 75% achieved using 5-second segments.