WHOOP for total sleep, Fitbit for REM? Study compares sleep trackers
In the quest for the ultimate night’s rest, wearable technologies like Fitbit, Garmin, and WHOOP have stepped up, promising to keep a close watch on our slumber. But how well do they really stack up against the rigorous standards of polysomnography. It turns out, they have strengths in some areas and weaknesses in others.
Getting a good night’s sleep is essential for our overall health and well-being. Traditional sleep studies, called polysomnography (PSG), are the gold standard for measuring sleep. However, PSGs are expensive, time-consuming, and require an overnight stay in a sleep lab.
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Wearable devices have emerged as a more convenient alternative for tracking sleep. These devices use sensors to monitor sleep patterns, including heart rate, movement, and blood oxygen levels.
A new study published in the Journal of Medical Internet Research (JMIR) compared the accuracy of three popular wearable devices (Fitbit Charge 4, Garmin Vivosmart 4, and WHOOP) to PSG. Armed with a battle plan outlined by the PRISMA guidelines, researchers embarked on a data-gathering crusade across prestigious databases, aiming to pit these gadgets against the heavyweight champion.
Device Analysis: Fitbit, Garmin, WHOOP
The study found that WHOOP and the Fitbit were pretty accurate in measuring total sleep time, with Garmin trailing behind. As far as sleep stages – all three struggled.
Metric | WHOOP | Fitbit Charge 4 | Garmin Vivosmart 4 |
|---|---|---|---|
Total Sleep Time (TST) | -1.4 min (underestimates) | +5.67 min (overestimates) | +46.9 min (overestimates) |
Light Sleep (LS) | -9.6 min (underestimates) | +37.6 min (overestimates) | +28 min (overestimates) |
Deep Sleep (DS) | -9.3 min (underestimates) | -19.33 min (underestimates) | +23.5 min (overestimates) |
REM Sleep | +21.0 min (overestimates) | +4.0 min (overestimates) | -12.55 min (underestimates) |
Sensitivity to Sleep (%) | 91.7% | 91.2% | 98.0% |
Specificity for Sleep (%) | 56.0% | 61.3% | 30.0% |
WHOOP demonstrated the highest accuracy in measuring total sleep time (TST), light sleep (LS), and deep sleep (DS), albeit with some discrepancies in rapid eye movement (REM) sleep, where it tended to show significant overestimation.
Fitbit Charge 4 showed commendable performance across multiple sleep stages, particularly in REM sleep, where it had the least disagreement with PSG. It also displayed higher sensitivity in detecting light sleep and deep sleep compared to the other devices.
The Garmin Vivosmart 4 exhibits high sensitivity to detecting sleep, which means it is very good at identifying when a person is actually sleeping. However, its accuracy for total sleep time is compromised by low specificity, which is its ability to correctly identify wake periods. Essentially, while the device is adept at detecting sleep, it struggles to distinguish when the user is awake. As far as sleep stage estimates, the device demonstrated moderate accuracy with significant variability.
What does this mean?
The results of this study suggest that wearable devices can provide a reasonable estimate of total sleep time. However, the accuracy for measuring individual sleep stages is not up to scratch. Fitbit Charge 4 appeared to be the most accurate overall, while WHOOP showed the least disagreement with PSG for most sleep stages except REM sleep. Garmin Vivosmart 4 was the least accurate device in the study.
Source:
Edited by Lorraine Buis; submitted 25.08.23; peer-reviewed by Anda Baharav, Klaus Martiny; final revised version received 01.02.24; accepted 01.02.24; published 27.03.24.
© An-Marie Schyvens, Nina Catharina Van Oost, Jean-Marie Aerts, Federica Masci, Brent Peters, An Neven, Hélène Dirix, Geert Wets, Veerle Ross, Johan Verbraecken. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 27.3.2024.
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