Can We Support Lucid Dreaming Practices with a Creative Deep Learning Algorithm and Immersive Virtual Reality Biofeedback System? - Kitson, Alexandra; DiPaola, Steve; Riecke, Bernhard E. (24th Annual CyberPsychology, CyberTherapy & Social Networking Conference (CyPsy24), 2019)
Lucid dreaming, awareness of dreaming while in a dream, allows the dreamer to recognize two different levels of awareness: the dream (actor) and the self (observer). The balance of these two levels is key to creative and flexible control of what happens in the lucid dream, and can enable the dreamer to explore their consciousness. Mastering this balance, however, is challenging and can take years to truly master. This poses a problem for those wanting to reap the benefits of lucid dreaming as well as researchers studying sleep and dreams since training takes time and a novice would not be able to become lucid reliably and consistently. Our proposed technological solution is to make use of immersive virtual reality (VR) for practicing awareness of the present moment, a skill that directly transfers to lucid dreaming, in particular becoming aware that one is dreaming. VR can be especially effective because of its many similarities to lucid dreaming itself, such as the ability to experience impossible or improbable worlds, the use of perceptual cues that are aimed to elicit a deep emotional involvement in the user, and the use of structured narratives conceived to trigger reflection and transformative insights. However, where lucid dreams are created with all of our past experiences and memories, VR does not have such privileged access to give us personalized feedback. We can, however, use our own physiological signals that are mapped to elements in the virtual environment to help generate content. A combination of physiological measures can be correlated with states of awareness, thereby directly showing participants’ awareness changing in real-time through creative visuals and audio. We present a proof-of-concept VR biofeedback system that uses our deep learning system, Painterly, to creatively and dynamically change the virtual environment from dream-like to clear or “lucid” as the participant’s physiological state changes from inattentive to focused. Using the Muse 2 headset, we collect data on brain waves through an electroencephalogram (EEG), heart rate through a photoplesmogram (PPG), and respiration through a combination of PPG and gyroscope. These data are then read via Bluetooth through an app, Muse Direct, which is then sent to a computer via Open Sound Control (OSC). These OSC messages are read and displayed in Unity, a game engine for VR. The raw data is filtered and mapped to a sliding-scale score ranging from 0 to 1, where 0 represents low lucidity and 1 represents high lucidity. This score is then used to dynamically change both the visuals and audio of the virtual environment, experienced by the participant through a head-mounted display and headphones. The participant can then playful interact with an artistic virtual representation of their own physiological data to learn how to self-regulate their own states and awareness. We hypothesize this system will help with self-regulation and increased or sustained lucid dreams, and thus provide a more direct way of teaching lucid awareness and opening up its many benefits. In future research, we will investigate this hypothesis.
Keywords: Riecke; Riecke_2019; alex-kitson; awe; bernhard-riecke; lucid-dreaming; lucid-loop; posterWithoutPaper; steve-dipaola; talkWithoutPaper