The accuracy of estimating sleep stages using heart rate and movement metrics is an interesting, and tenuous, subject. WRT to Fitbit and Oura the TLDR is that Fitbit and Oura aren’t accurate for slow wave (Deep Sleep) or REM. However, Fitbit is better at REM detection [1][2] than Oura.
While sleep staging can be useful for identifying case sleep disorders, we know that the brain self-optimizes the stages of sleep you go through.
So, what’s far more important than worrying about your rem or deep is optimizing getting time in any stage of sleep. Each stage is critical in a different way.
If you care about improving your performance the measures you should care about—backed by strong scientific consensus and a plurality of randomized evidence—are sleep debt and where you are in your circadian rhythm. Sleep scientists call this the two factor model
This reality drove us to create a sleep improvement app, called Rise ([https://www.risescience.com](https://www.risescience.com/)). We started both our research and company initially for elite athletes. We tell them what to do to improve their sleep tonight based on science. It's currently being used by both professional and collegiate teams across the NFL, MLB, NBA, MLS, and NCAAF.
We've been taking what we've learned from athletes and adapting for us regular folk.
It's exciting to see specific validation for our industry.
We've seen a similar phenomenon with athletes, which drove us to create a sleep improvement app, called Rise Science (https://www.risescience.com), for athletes that tells them what to do to improve their sleep tonight based on science. It's currently being used by both professional and collegiate teams across the NFL, MLB, NBA, MLS, and NCAAF.
We're now taking what we've learned from athletes and adapting it so anyone can engage in a lifelong practice of healthy sleep. If you're interested in helping test the early beta version of our app sign up here: http://bit.ly/hacker-friends
(for those interested in similar studies, here's a related paper from a friend of Rise at Stanford, where they quantify the impact of less sleep on cognitive performance using web search interactions as a proxy: http://timalthoff.de/docs/althoff-2017-population_scale_phys...)
While sleep staging can be useful for identifying case sleep disorders, we know that the brain self-optimizes the stages of sleep you go through.
So, what’s far more important than worrying about your rem or deep is optimizing getting time in any stage of sleep. Each stage is critical in a different way.
If you care about improving your performance the measures you should care about—backed by strong scientific consensus and a plurality of randomized evidence—are sleep debt and where you are in your circadian rhythm. Sleep scientists call this the two factor model
This reality drove us to create a sleep improvement app, called Rise ([https://www.risescience.com](https://www.risescience.com/)). We started both our research and company initially for elite athletes. We tell them what to do to improve their sleep tonight based on science. It's currently being used by both professional and collegiate teams across the NFL, MLB, NBA, MLS, and NCAAF.
We've been taking what we've learned from athletes and adapting for us regular folk.
If you're interested in joining our beta, sign up here: [http://bit.ly/hacker-friends](http://bit.ly/hacker-friends)
[1] [https://www.ncbi.nlm.nih.gov/pubmed/28323455](https://www.nc...
[2] [https://www.ncbi.nlm.nih.gov/pubmed/29235907](https://www.nc...