Published On May 19, 2024
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🔴 Whoop Strap 4.0: https://join.whoop.com/QuantifiedScie...
($30 off any new WHOOP membership)
🔴 Eight sleep 350$/200$ (€) discount*: https://eight-sleep.ioym.net/TheQuant... + add code “UNBOXTHERAPY” or “TQS” for full discount
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📸My Gear* (paid links, supports the channel and doesn’t cost you any more)📸
Camera body (main): https://geni.us/SonyA6600_body
Camera lens (main): https://geni.us/SigmaContemporary
Camera (B-roll 1): https://geni.us/Sony_ZVE1
Camera (B-roll 2): https://geni.us/CanonEosM50MarkII and https://geni.us/Sony_ZVE10
Light: https://geni.us/Godox_VL150
Softbox: https://geni.us/NiceFotoSoftbox
Light stand: https://geni.us/WalimexLightstand
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Reference devices:
ZMax + Dreamento: https://www.biorxiv.org/content/10.11... & https://github.com/dreamento/dreamento
Polar H10: https://pubmed.ncbi.nlm.nih.gov/31004...
🔴 Polar H10: https://geni.us/hnXc
Spreadsheet with all information: https://docs.google.com/spreadsheets/...
Note, as a starting point I used a table from a very nice paper: Birrer et al. 2024 Table 1 (https://www.ncbi.nlm.nih.gov/pmc/arti...)
Timestamps:
00:00 Quick Intro
00:31 Sleep - Wakefulness Detection (Scientific Papers)
04:33 Sleep Stage Detection (Scientific Papers)
10:59 Most Recent Device Testing (Own Testing, Pt1)
14:09 Most Recent Device Testing (Own Testing, Pt2)
15:27 Conclusions
I went through hundreds of scientific publications to find out which the best sleep stage trackers are that money can buy, depending on your budget. Is it Apple, Google, Samsung, Oura, Garmin, Polar or maybe Fitbit. Well, today you are going to find out! This is a video I’ve been wanting to make for a long time, and the results are super interesting. It also shows us some major problems with sleep tracking I have not addressed in my previous videos. A spreadsheet with all the statistics and references I base my findings on is in the description below, and of course there are timestamps on this video's timeline to make things easier for you.
Detecting whether you are asleep or awake is what wearables would traditionally measure in the early 2010s, with the launch of the first Fitbit Tracker for instance. However, during that same decade more and more companies tried to do something much more complicated: tracking the sleep stages defined by scientists, albeit in a slightly simplified form, which were termed light sleep, deep sleep and REM sleep. This is actually really hard, since these are usually studied in the lab by measuring brain waves, eye movements, and muscle movements. Instead, a wearable has to do it based on just your heart beats and movements. In my testing I’ve seen that wearables are becoming much better at this, and more people than ever seem to be using them to keep track of their sleep patterns. Over the last few years I’ve also found that it’s becoming more and more accepted in the scientific community to use smartwatches and smart bands in sleep research. However, for both consumers and scientists it’s important to know which devices are good at tracking stages and which are not so reliable, since some are quite bad. Luckily, scientists are recognizing the value in actually testing the performance of wearables using polysomnography or EEG, giving us an idea which smartwatches are good, and which are not. However, they usually test only one or a few devices at a time, so similar to before I went through literature, and extracted the results from all papers I could find to give us a good overview of the performance of different devices.
Intro Music from #Uppbeat (free for Creators!):
https://uppbeat.io/t/moire/new-life
License code: OBLD6VBBCTRDFZQP