Key result
EEG measures at the sensor level generally exhibited higher average intraclass correlation coefficients than those at the source level for assessing driving fatigue.
Why the study?
Measures' reliability has not been investigated across brain states, leaving unknown how reliable EEG measures are during the transition from an alert to a fatigue state while driving.
Observational
EEG measures at the sensor level generally show higher reliability than source level measures for monitoring driving fatigue over a one-week interval.
Answers are grounded in this paper and cite their sources.
Measures' reliability across alert-to-fatigue states remains unclear in driving; leaves open standardization needs for neuroengineering research.
Reliability investigation of measures is important in studies of brain science and neuroengineering. Measures' reliability hasn't been investigated across brain states, leaving unknown how reliable the measures are in the context of the change from alert state to fatigue state during driving. To compensate for the lack, we performed a comprehensive investigation. A two-session experiment with an interval of approximately one week was designed to evaluate the reliability of the measures at both sensor and source levels. The results showed that the average intraclass correlation coefficients (ICCs) of the measures at the sensor level were generally higher than those at the source level, except for the directed between-region measures. Single-region measures generally exhibited higher average ICCs relative to between-region measures. The exploration of brain network topology showed that nodal metrics displayed highly varying ICCs across regions and global metrics varied associated with nodal metrics. Single-region measures displayed higher ICCs in the frontal and occipital regions while the between-region measures exhibited higher ICCs in the area involving frontal, central and occipital regions. This study provides an appraisal for the measures' reliability over a long interval, which is informative for measure selection in practical mental monitoring.
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Harvy et al. (2022) conducted an observational in Driving fatigue. EEG measures was evaluated on Intraclass correlation coefficients (ICCs) of EEG measures. EEG measures at the sensor level generally exhibited higher average intraclass correlation coefficients than those at the source level for assessing driving fatigue.
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