A validation study of Fitbit Charge 2™ compared with polysomnography in adults

Area of Science:

• Sleep Science
• Wearable Technology
• Biomedical Engineering

Background:

• Consumer wearable devices are increasingly used for health monitoring.
• Accurate sleep stage tracking is crucial for understanding sleep quality and health.
• Polysomnography (PSG) is the gold standard for sleep assessment, but is resource-intensive.

Purpose of the Study:

• To evaluate the performance of the Fitbit Charge 2™ consumer wristband against PSG for sleep/wake state and sleep stage composition measurement.
• To compare Fitbit Charge 2™ sleep data with PSG in healthy adults.

Main Methods:

• 44 healthy adults underwent a single overnight recording with both PSG and Fitbit Charge 2™.
• Data were analyzed using paired t-tests, Bland-Altman plots, and epoch-by-epoch analysis.
• Participants with periodic limb movement of sleep (PLMS) were analyzed separately.

Main Results:

• Fitbit Charge 2™ demonstrated high sensitivity (0.96) for detecting sleep but lower specificity (0.61) for wake.
• Accuracy was good for light sleep (N1+N2, 0.81) and REM sleep (0.74), but limited for deep sleep (N3, 0.49).
• The device overestimated total sleep time and light sleep, while underestimating deep sleep and sleep onset latency.

Conclusions:

• Fitbit Charge 2™ shows potential for sleep-wake state and sleep stage estimation, particularly for REM sleep, compared to PSG.
• Limitations exist in deep sleep (N3) detection accuracy.
• Further investigation is warranted in diverse settings and populations to assess Fitbit Charge 2™ reliability.