The limitations of wrist actigraphy for differentiating sleep from wake are worse in those with insomnia, as "subjects who are awake but lie motionless can be classified incorrectly as being asleep, and thus the technique is biased toward overestimating time to sleep, which may lead to incorrectly minimizing the severity of sleep disturbances." Like other sleep sensors utilizing actigraphy, Oura in most individuals can't accurately differentiate between times when you are lying still but awake and when you are lying still and asleep. Overall, Oura had 96% sensitivity for detecting sleep, 48% specificity for detecting wakefulness, 65% agreement in detecting "light sleep", 51% agreement in detecting "deep sleep", and 61% agreement in detecting REM sleep, relative to PSG. These data suggest that the Oura Ring is virtually useless in telling you if you are in REM sleep versus deep or light sleep.Īs the authors noted, "Distinguishing sleep stages such as REM and N3 with non-EEG based systems has been challenging and is a goal of several commercial sleep-trackers, with mixed success." When the ring misclassified PSG REM sleep, the algorithm usually classified the epoch as "light sleep" (76%). It also accurately detected 61% of REM sleep epochs, with an overall overestimation of PSG REM sleep (by about 17 min). The ring accurately detected "light" and "deep" sleep in 65% and 51% of the sleep epochs, respectively. Metrics were compared using Bland-Altman plots and epoch-by-epoch analysis. Sleep data were recorded using the Oura ring and standard PSG on a single laboratory overnight. The SRI researchers studied 41 healthy adolescents and young adults (average age 17). The paper is entitled "The Sleep of the Ring: Comparison of the ŌURA Sleep Tracker Against Polysomnography," and it was written by researchers at SRI International, a research consortium in Menlo Park, California, with no ties to the company.Īnother paper that used to be touted on the Oura Ring website (but is no longer referenced on the site) utilized home PSG recordings and was done by an Oura employee. So what does the SRI paper Oura likes to quote as proving its accuracy say? Science Behind the Analytics: Detecting Sleep Stages However, information about sleep stage composition, fundamental in studying sleep and sleep disorders, is not provided." Most importantly, actigraphy relies on a single sensor, an accelerometer, and thus it provides a measure of motion from which it predicts sleep and wake states. "Compared to PSG, actigraphy has high sensitivity (ability to detect sleep) although specificity (ability to detect wakefulness) is lower ( Marino et al., 2013 Sadeh, 2011), with a wide range of accuracy, depending on the amount of night-time wakefulness ( Paquet, Kawinska, & Carrier, 2007), the algorithms used and the particular population studied ( Van de Water, Holmes, & Hurley, 2011).
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