Targeted lucidity reactivation implemented in an open-source watchOS app

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.