Heart rate detection by Fitbit ChargeHR^™ : A validation study versus portable polysomnography

Area of Science:

• Physiological monitoring
• Wearable technology validation
• Sleep science

Background:

• Consumer smartbands collect physiological data, including heart rate (HR), but their data quality and validation for research are often debated.
• Rigorous validation of wearable devices is crucial for their reliable application in clinical and research settings.

Purpose of the Study:

• To investigate the reliability and accuracy of heart rate (HR) detection using the Fitbit ChargeHR (FBCHR) in a naturalistic setting.
• To compare FBCHR photoplethysmographic HR data with concurrent portable polysomnography (pPSG) derived HR across different vigilance states.

Main Methods:

• Collected concurrent portable polysomnography (pPSG) and Fitbit ChargeHR (FBCHR) photoplethysmographic data from 25 healthy young adults over ≥12 hours.
• Validated pPSG-derived HR for each 1-min epoch and downloaded FBCHR HR data via its API.
• Analyzed data for accuracy using mean differences, Pearson's correlation coefficients, and Bland-Altman analysis across vigilance states and heart rate ranges.

Main Results:

• The FBCHR demonstrated good overall accuracy in estimating HR, with a mean difference of -0.66 (0.04) bpm compared to pPSG, and an overall Pearson's r of 0.93.
• Correlation coefficients were higher during all sleep stages (REM, N1, N2, N3) than during wakefulness.
• Accuracy was higher for HRs <100 bpm (r=0.84) than for HRs >100 bpm (r=0.374), with Bland-Altman analysis supporting higher accuracy during sleep.

Conclusions:

• The Fitbit ChargeHR (FBCHR) exhibits relatively high accuracy in detecting pulse rate, particularly during sleep.
• The device's accuracy suggests its suitability for sleep-related research applications in healthy individuals under free-living conditions.
• Further validation across diverse populations and conditions is recommended for broader clinical applications.