A new EEG biomarker of neurobehavioural impairment and sleepiness in sleep apnea patients and controls during extended wakefulness

•We analysed resting, awake EEG data using two qEEG methods, power spectral analysis (PSA) and detrended fluctuation analysis (DFA), and assessed their ability to yield EEG biomarkers of neurobehavioural impairment and sleepiness.•PSA and DFA biomarkers correlated with impaired performance and increased sleepiness, and baseline measures of the DFA scaling exponent, but not power spectra, were associated with impaired simulated driving after extended wakefulness in obstructive sleep apnea (OSA) patients.•The DFA scaling exponent has potential as a useful biomarker of performance failure which can be used as an alternative to conventional power spectra.

ObjectiveTo explore the use of detrended fluctuation analysis (DFA) scaling exponent of the awake electroencephalogram (EEG) as a new alternative biomarker of neurobehavioural impairment and sleepiness in obstructive sleep apnea (OSA).MethodsEight patients with moderate–severe OSA and nine non-OSA controls underwent a 40-h extended wakefulness challenge with resting awake EEG, neurobehavioural performance (driving simulator and psychomotor vigilance task) and subjective sleepiness recorded every 2-h. The DFA scaling exponent and power spectra of the EEG were calculated at each time point and their correlation with sleepiness and performance were quantified.ResultsDFA scaling exponent and power spectra biomarkers significantly correlated with simultaneously tested performance and self-rated sleepiness across the testing period in OSA patients and controls. Baseline (8am) DFA scaling exponent but not power spectra were markers of impaired simulated driving after 24-h extended wakefulness in OSA (r = 0.738, p = 0.037). OSA patients had a higher scaling exponent and delta power during wakefulness than controls.ConclusionsThe DFA scaling exponent of the awake EEG performed as well as conventional power spectra as a marker of impaired performance and sleepiness resulting from sleep loss.SignificanceDFA may potentially identify patients at risk of neurobehavioural impairment and assess treatment effectiveness.