TABLE 1

Fitness tracking devices vs conventional methods of evaluating sleep

DeviceComparatorNStudy populationResults
Fitbit13Polysomnography and actigraphy24Healthy adults with no history of symptoms of sleep disorders
Mean age 26.1
Sensitivity for sleep 97.8%
Specificity for wakefulness 19.8%
Overestimated total sleep time and sleep efficiency and underestimated wake time after sleep onset
Fitbit Ultra14Polysomnography and actigraphy63Children and adolescents undergoing overnight clinical polysomnography
Mean age 9.7
‘Normal’ mode overestimated total sleep time and sleep efficiency and underestimated wake time after sleep onset
‘Sensitive’ mode underestimated total sleep time and sleep efficiency and overestimated wake time after sleep onset
Jawbone UP15Polysomnography65Healthy adolescents
Mean age 15.8
Overestimated total sleep time and sleep efficiency and underestimated wake time after sleep onset, no difference in sleep onset latency
No clear correlation between ‘light’ and ‘deep’ sleep and conventional polysomnographic sleep stages
Jawbone UP16Polysomnography28Midlife women
Mean age 50.1
Sensitivity for sleep 96%
Specificity for wakefulness 37%
Overestimated total sleep time and sleep onset latency and underestimated wake time after sleep onset
Jawbone UP17Polysomnography and actigraphy64Children and adolescents with suspected sleep-disordered breathing
Mean age 8.4
Sensitivity for sleep 92%
Specificity for wakefulness 66%
No difference from polysomnography on total sleep time, sleep efficiency, sleep onset latency, and wake time after sleep onset
Compared with actinography, overestimated sleep onset latency and underestimated wake time after sleep onset