Fitbit Displays Accuracy Compared to Polysomnography Measures in Children and Adolescents

April 28, 2021
Victoria Johnson
Victoria Johnson

Victoria Johnson, Assistant Editor for NeurologyLive, joined the MJH Life Sciences team in October 2020. Follow her on Twitter @VictoriaJNeuro or email her at

Researchers compared sleep measures between the Fitbit Charge 3, the Actigraph GT9X accelerometer, and polysomnography.

Data from a recent study suggest that the Fitbit Charge 3 wrist device provided comparable sleep estimates to polysomnography (PSG) and the Actigraph GT9X accelerometer, and in some cases performed better, in children and adolescents.

Researchers found that the Fitbit underestimated total sleep time (TST) by 6.1 minutes (standard deviation [SD], 36.2; absolute mean bias [AMB], 27.7 [SD, 23.8]) and the Actigraph underestimated TST by 31.5 minutes (SD, 34.6; AMB, 38.2 [SD, 26.9]). The Fitbit overestimated sleep efficiency (SE) by 3.0% (SD, 7.7; AMB, 6.3 [SD, 5.4]) and the Actigraph overestimated SE by 12.9% (SD, 7.7; AMB, 13.2 [SD, 6.7]).

“The inability [of wrist-based accelerometry] to accurately detect wakefulness during a sleep period, especially among those who experience greater night awakenings and movement is commonly noted as a limitation in research studies, yet few advances have been made to improve this limitation,” wrote first author Sarah Burkart, MPH, PhD, postdoctoral research fellow, University of South Carolina, Arnold School of Public Health, and colleagues.

Burkart and colleagues analyzed data from 56 participants with an average age of 9.2 years (standard deviation [SD], 3.3) that wore a Fitbit and an Actigraph on their nondominant wrist concurrently with PSG performed during an overnight observation at a children’s sleep laboratory. The participants were 55% female, 57% Black, and 79 individuals were diagnosed with obstructive sleep apnea (OSA).

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In addition to the aforementioned overestimations in TST by the Fitbit and Actigraph, there was a statistically significant positive trend in the Bland-Altman data between the Actigraph and PSG with a slope of 0.33 ([SD, 0.10; 95% CI, 0.13-0.53]; P = .002), suggesting that the Actigraph underestimated TST as TST increased.

As for the 2 devices’ sleep efficiency overestimations, there was a statistically significant positive trend in the Bland-Altman data between the Fitbit and PSG with a slope of 0.81 ([SD, 0.08; 95% CI, 0.65-0.98]; P <.001). A similar trend was seen with Actigraph and PSG (slope, 0.37 [SD, 0.13; 95% CI, 0.12-0.63]; P = .005), suggesting that both devices underestimated SE at higher values of SE.

The Fitbit overestimated wake after sleep onset (WASO) by 18.8 minutes (SD, 19.5; AMB, 23.9 [SD, 13.1]) and the Actigraph overestimated WASO by 56.1 minutes (SD, 33.6; AMB, 54.7 [SD, 33.2]). There was a statistically significant positive trend for both the Fitbit (slope, 0.68 [SD, 0.14; 95% CI, 0.39-0.97]; P <.001) and the Actigraph (slope, 0.45 [SD, 0.21; 95% CI, 0.04-0.87]; P = .034) that suggested both devices tended to underestimate WASO at higher values of WASO.

The Fitbit underestimated sleep onset (SOn) by 1.2 minutes (SD, 25.8; AMB, 13.9 [SD, 21.7]) and the Actigraph underestimated SOn by 10.2 minutes (SD, 34.5; AMB, 18.1 [SD, 31.1]). Actigraph had a significant positive trend with PSG (slope, 0.36 [SD, 0.10; 95% CI, 0.16-0.55]; P <.05), suggesting it underestimated SOn at later onset times.

The Fitbit overestimated sleep offset (SOf) by 6.0 minutes (SD, 23.3; AMB, 12.0 [SD, 20.5]) and the Actigraph overestimated SOf by 10.5 minutes (SD, 18.1; AMB, 12.6 [SD, 19.8]). No statistically significant trends with PSG were seen for either device.

“Overall, findings suggest that a multichannel device (Fitbit Charge 3) performs as well as and in some instances better than a single-channel device (Actigraph GT9X) for measuring sleep when compared with PSG in children and adolescents with diagnosed sleep disorders,” Burkart and colleagues wrote.

“This newer technology may improve upon the limitations of single-channel devices that solely rely on accelerometry to detect sleep and wakefulness. Further testing is needed in healthy and other clinical samples of youth in a free-living environment and over several nights,” they concluded.

Burkart S, Beets MW, Armstrong B, et al. Comparison of multichannel and single-channel wrist-based devices with polysomnography to measure sleep in children and adolescents. J Clin Sleep Med. 2021;17(4):645-652. doi: 10.5664/jcsm.8980