Both devices however, are significantly flawed when measuring sleep stages such as deep sleep and REM sleep, with Whoop being the better of the two. Oura was less accurate for deep sleep with an agreement of only 51% with polysomnography and 61% for REM sleep.įrom these results, we can confidently say that in general, both devices are accurate enough in measuring basic sleep metrics such as time spent asleep and time awake. However for estimating minutes awake after sleep onset it was only similar in around 51%. Whoop was the more accurate of the two at 68% similarity to polysomnography when measuring deep sleep and 70% for REM sleep. When it comes to more detailed metrics the accuracy of these devices starts to get less reliable. Oura was mostly accurate in estimating the time it takes to fall asleep (sleep onset latency or SOL), how long you spend awake after falling asleep (wakefulness after sleep onset or WASO) and total sleep time. Whoop was shown to give a small overestimation of total sleep time on average but did not vary significantly. In this article I focus primarily on Whoop and Oura as they are the most common devices owned by Span users.īoth Whoop and oura give reliable measurements of simple sleep measurement such as total sleep and wake time. There have been a few studies comparing different wearables to polysomnography. In order to assess the accuracy of sleep metrics obtained from a wearable device, they are compared to that gold standard. The gold standard for sleep tracking is a lab test called polysomnography. How accurate are my wearable sleep metrics? Always correlate your data with other related metrics and more importantly, how you feel.When interpreting sleep stage metrics such as deep and REM sleep you should focus more on the trend rather than the number .Wearables are accurate enough when measuring basic sleep metrics such as time spent asleep and time awake . Wearables are not as accurate as lab tests yet but they can still be useful .
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