Fitbit charge 35/19/2023 Further insight is needed to determine factors potentially affecting device performance, such as accuracy and reliability (consistency of performance over time), in different samples and conditions.įitbit Wearable sleep trackers accuracy adolescence consumer sleep technology insomnia. Our results are in line with a general trend in the literature, suggesting better performance for the recently introduced multi-sensor devices compared to motion-only devices, although further developments are needed to improve accuracy in sleep stage classification and wake detection. The magnitude of the heart rate acceleration/deceleration between consecutive PSG epochs was an important factor affecting FC3 classifications of sleep stages. Not only will this stop you having to pocket your device. Body mass index was positively associated with FC3-PSG discrepancies in wake after sleep onset (R 2 =. One of the most notable features is that the Charge 3 is Fitbits first waterproof activity tracker. Similar results were found in the sample of adolescents with insomnia symptoms. Epoch-by-epoch analysis showed sleep-stage sensitivity (average proportion of PSG epochs correctly classified by the device for a given sleep stage) of 68% for wake, 78% for "light" sleep, 59% for "deep" sleep, and 69% for rapid eye movement (REM) sleep in healthy sleepers. No significant systematic bias was detected for sleep efficiency and sleep onset latency. Proportional biases were detected for "light" and "deep" sleep duration, resulting in significant underestimation of these parameters for those participants having longer PSG N1+ N2 and N3 durations, respectively. In the sample of healthy adolescents, FC3 systematically underestimated PSG total sleep time by about 11 min and sleep efficiency by 2.5%, and overestimated wake after sleep onset by 9 min. The influence of several factors potentially affecting FC3 performance (e.g., sex, age, body mass index, firmware version, and magnitude of heart rate changes between consecutive PSG epochs) was also tested. ![]() Discrepancy analysis, Bland-Altman plots, and epoch-by-epoch analyses were used to evaluate FC3 performance. Single-night PSG and FC3 sleep outcomes were compared in thirty-nine adolescents (22 girls 16-19 years), 12 of whom presented with clinical/subclinical DSM-5 insomnia symptoms (7 girls). We evaluated the performance of Fitbit Charge 3™ (FC3), a multi-sensor commercial sleep-tracker, for measuring sleep in adolescents against gold-standard laboratory polysomnography (PSG).
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