Garmin Is BAD At Sleep Tracking. And That's Okay!
In a Nutshell
Garmin watches consistently rank among the worst for sleep stage tracking across three independent evidence sources: a University of Salzburg study against polysomnography, personal EEG testing, and a meta-analysis of scientific literature. While Garmin's heart rate measurements during sleep are reliable and correlate well with reference devices, sleep stage accuracy for deep sleep, REM, and awake time is notably poor compared to competitors like Aura Ring, Whoop, Pixel Watch, and Apple Watch. This stems from Garmin's design priority on sports tracking features rather than sleep analysis, making their watches suitable for users who value GPS, battery life, and ecosystem connectivity over precise sleep staging.
These notes were generated by AI and may contain inaccuracies.
Your Garmin watch is likely quite bad at sleep stage tracking compared to the competition. The speaker will show three lines of scientific evidence for this, but will also demonstrate what Garmin watches are good at during the night and why this might not be a major issue for some users.
Sleep tracking performance is usually the same across Garmin devices. Every Garmin device will perform more or less the same for sleep stage tracking, whether it's a Fenix device, Garmin X1, or Venue series.
A sleep study conducted with the University of Salzburg involved 18 people over approximately four to five nights wearing different wearables. The devices tested included Garmin (plotted in red), Polar, Aura, Whoop, Apple, Google, and the Circle Plus ring (plotted in black).
The wearables were tested by comparing them against polysomnography, the gold standard sleep stage tracking. This involves electrodes measuring heart rate, eye movements, and brain waves to get the most reliable measurements of sleep stages.
Performance was compared using Cohen's Kappa (horizontal axis, higher is better) and sensitivity (vertical axis). The analysis took the average value per person, with each dot representing one person for one wearable across all nights. The average performance of all devices was subtracted for each person, meaning devices to the left of zero performed worse than average, and those to the right performed better than average.
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