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Verfasst von:Mallela, Rishabh [VerfasserIn]   i
 Mallett, Remington [VerfasserIn]   i
Titel:Targeted lucidity reactivation implemented in an open-source watchOS app
Verf.angabe:Rishabh Mallela, and Remington Mallett
E-Jahr:2024
Jahr:2024-10-17
Umfang:5 S.
Fussnoten:Gesehen am 06.11.2024
Titel Quelle:Enthalten in: International journal of dream research
Ort Quelle:Heidelberg : Univ.-Bibliothek, 2008
Jahr Quelle:2024
Band/Heft Quelle:17(2024), 2 vom: Okt., Seite 143-147
ISSN Quelle:1866-7953
Abstract:The induction of lucid dreams in ecological settings is critical for a comprehensive understanding of their phenomenology, neural underpinnings, and feasibility for therapies. Recent methods have been developed to deliberately induce lucid dreams, but they are highly dependent on laboratory equipment. Namely, a method known as targeted lucidity reactivation involves pairing sensory cues with a state of mental reflection, tracking sleep stages using polysomnography, and playing sensory cues in REM sleep to induce lucidity. Playing cues during specific sleep stages is a critical component of targeted lucidity reactivation, and to-date there are very limited ways to derive sleep stages without polysomnography or proprietary wearables. To resolve this limitation and promote the testing of targeted lucidity reactivation in a variety of settings, we developed an open-source iOS/watchOS application that performs the entire targeted lucidity reactivation procedure (pre-sleep training, real-time sleep staging, and REM cueing). Critically, the app includes a custom real-time sleep staging algorithm to identify REM sleep using measures derived from the Apple Watch and accessible to any developer. The current study offers a technical framework for future research investigating the feasibility of inducing lucid dreams outside the lab using everyday technology.
DOI:doi:10.11588/ijodr.2024.2.100797
URL:kostenfrei: Volltext: https://doi.org/10.11588/ijodr.2024.2.100797
 kostenfrei: Volltext: https://journals.ub.uni-heidelberg.de/index.php/IJoDR/article/view/100797
 DOI: https://doi.org/10.11588/ijodr.2024.2.100797
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:application
K10plus-PPN:1907791949
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