Mental fatigue, a common consequence of cognitively demanding work, impairs concentration and well-being, posing long-term health risks. Distinct from drowsiness, mental fatigue is reliably measured with EEG, yet conventional setups remain too cumbersome for everyday use. To overcome this barrier, this study investigates whether EEG headphones can detect mental fatigue and recovery across two common digital break activities: playing a video game and browsing social media. We conducted an experiment with consecutive task sessions and an intermittent break, collecting self-report, performance, and EEG data. Our results show that EEG headphones can detect mental fatigue and recovery dynamics via relative alpha power, and differentiate recovery effects between break types. Social media proved more restorative than gaming, with effects persisting into the subsequent task. These findings establish needed working principles for using headphone-EEG in naturalistic fatigue and recovery research, providing a foundation for future studies.
ACM CHI Conference on Human Factors in Computing Systems