SleepStim is a framework for automatically recording sleep physiology and presenting sensory stimuli in sleep, using consumer smartphones and smartwatches.
Sounds played during specific phases of sleep can be used to augment cognition. For example, in Targeted Memory Reactivation (TMR), sounds are used to induce replay of specific memories in sleep, leading to stronger memory and less forgetting. A related technique uses sounds to enhance sleep-related oscillations in the brain, which may benefit sleep quality. However these techniques usually require a staffed sleep lab, which limits their utility.
SleepStim is designed to automate sound stimulation during sleep, so that people can use it in their own home. We accomplish this using a smartwatch to monitor the participant while sleeping, and a novel algorithm which uses the smartwatch data to calculate the participant's sleep stage in real time. Sounds can then be played when the participant enters deep (N3) or REM sleep.
SleepStim also enables researchers to collect raw sleep data while participants use the device at home. Currently, SleepStim is being used for a number of research projects involving stroke treatment, treatment of memory problems in older adults, and inducing lucid dreams.
SleepStim was originally developed at the Cognitive Neuroscience Lab at Northwestern University and is now supported by Nathan Whitmore in Fluid Interfaces.
For more details, please see the Github page:
https://github.com/nathanww/home-tmr
Publications:
Whitmore, N. W., Harris, J. C., Kovach, T. & Paller, K. A. Improving Memory via Automated Targeted Memory Reactivation during Sleep. Journal of Sleep Research 2022.06.28.497977 (2022) doi:10.1101/2022.06.28.497977.