Abstract
Background: Despite the importance of regular sleep patterns being well-known throughout society, a growing number of people claim to be sleep-deprived. There is a need to identify a simple and unobtrusive method in which people can accurately track their sleep to monitor changes and track how their sleep affects their daytime function. Methods: Here, we compared two at-home sleep monitors, the Zeo EEG headband system and the OURA physiological ring, in twenty-seven healthy young adults to determine their relative accuracy in classifying the various sleep stages. The two devices track sleep differently. The ring relies on hand movements and hemodynamic and respiratory changes in the body, while the headband system analyzes forehead EEG brain activities. Subjects wore both devices to sleep for 3-5 nights. Total sleep time, latency to sleep, time in wake, percentage and time in REM, percentage and time in light sleep, and percentage and time in deep sleep were recorded. The means and mean standard deviations of the two systems' sleep variables were assessed. Results: Compared to the EEG headband, the ring overestimated the awakening episodes' duration and underestimated the sleep latency. The ring was also more variable in capturing the total awakening episodes and deep sleep duration. Notably, the EEG headband gave information about the number of awakenings, which the ring does not report. Conclusion: Sleep quality, or the lack thereof, has relevant applications in physical rehabilitation. The results of the study point to the need to continue developing reliable and simple methods to monitor night sleep quality. While this study looked at individuals who do not have sleep dysfunction, it is possible that the discrepancies between the two sleep monitoring systems would be wider among people with sleep disorders.
Recommended Citation
Chong, Raymond; Willis, Alex; Kakaiya, Sonya; Schambach, Casey; Todd, Carla; and Young, Alex
(2023)
"Comparison of Two At-Home Sleep Monitoring Technologies,"
Asian Journal of Physical Therapy: Vol. 1:
No.
2023, Article 5.
Available at:
https://digitalcommons.lmunet.edu/ajpt/vol1/iss2023/5