Performance of the Dreem 2 EEG headband, relative to polysomnography, for assessing sleep in Parkinson’s disease

Abstract

Goal and aimsTo pilot the feasibility and evaluate the performance of an EEG wearable for measuring sleep in individuals with Parkinson’s disease. Focus technologyDreem Headband, Version 2. Reference technologyPolysomnography. SampleTen individuals with Parkinson’s disease. DesignIndividuals wore Dreem Headband during a single night of polysomnography. Core analyticsComparison of summary metrics, bias, and epoch-by-epoch analysis. Additional analytics and exploratory analysesCorrelation of summary metrics with demographic and Parkinson’s disease characteristics. Core outcomesSummary statistics showed Dreem Headband overestimated several sleep metrics, including total sleep, efficiency, deep sleep, and rapid eye movement sleep, with an exception in light sleep. Epoch-by-epoch analysis showed greater specificity than sensitivity, with adequate accuracy across sleep stages (0.55-0.82). Important supplemental outcomesGreater Parkinson’s disease duration and rapid eye movement behavior were associated with more wakefulness, and worse Parkinson’s disease motor symptoms were associated with less deep sleep. Core conclusionThe Dreem Headband performs similarly in Parkinson’s disease as it did in non-Parkinson’s disease samples and shows promise for improving access to sleep assessment in people with Parkinson’s disease.