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

David Andrés González, Duo Wang, Erin Pollet, Angel Velarde, Sarah Horn, Pablo Coss, Okeanis Vaou, Jing Wang, Chengdong Li, Sudha Seshadri, Hongyu Miao, Mitzi M. Gonzales

Producción científica: Articlerevisión exhaustiva


Goal and aims: To pilot the feasibility and evaluate the performance of an EEG wearable for measuring sleep in individuals with Parkinson's disease. Focus technology: Dreem Headband, Version 2. Reference technology: Polysomnography. Sample: Ten individuals with Parkinson's disease. Design: Individuals wore Dreem Headband during a single night of polysomnography. Core analytics: Comparison of summary metrics, bias, and epoch-by-epoch analysis. Additional analytics and exploratory analyses: Correlation of summary metrics with demographic and Parkinson's disease characteristics. Core outcomes: Summary 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 outcomes: Greater 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 conclusion: The 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.

Idioma originalEnglish (US)
Páginas (desde-hasta)24-30
Número de páginas7
PublicaciónSleep Health
EstadoPublished - feb 2024

ASJC Scopus subject areas

  • Health(social science)
  • Neuropsychology and Physiological Psychology
  • Behavioral Neuroscience
  • Social Sciences (miscellaneous)


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