Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study (Preprint) Article Swipe
Benjamin Stucky
,
Ian D. Clark
,
Yasmine Azza
,
Walter Karlen
,
Peter Achermann
,
Birgit Kleim
,
Hans‐Peter Landolt
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2196/preprints.26476
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2196/preprints.26476
BACKGROUND Multisensor fitness trackers offer the ability to longitudinally estimate sleep quality in a home environment with the potential to outperform traditional actigraphy. To benefit from these new tools for objectively assessing sleep for clinical and research purposes, multisensor wearable devices require careful validation against the gold standard of sleep polysomnography (PSG). Naturalistic studies favor validation. OBJECTIVE This study aims to validate the Fitbit Charge 2 against portable home PSG in a shift-work population composed of 59 first responder police officers and paramedics undergoing shift work. METHODS A reliable comparison between the two measurements was ensured through the data-driven alignment of a PSG and Fitbit time series that was recorded at night. Epoch-by-epoch analyses and Bland-Altman plots were used to assess sensitivity, specificity, accuracy, the Matthews correlation coefficient, bias, and limits of agreement. RESULTS Sleep onset and offset, total sleep time, and the durations of rapid eye movement (REM) sleep and non–rapid-eye movement sleep stages N1+N2 and N3 displayed unbiased estimates with nonnegligible limits of agreement. In contrast, the proprietary Fitbit algorithm overestimated REM sleep latency by 29.4 minutes and wakefulness after sleep onset (WASO) by 37.1 minutes. Epoch-by-epoch analyses indicated better specificity than sensitivity, with higher accuracies for WASO (0.82) and REM sleep (0.86) than those for N1+N2 (0.55) and N3 (0.78) sleep. Fitbit heart rate (HR) displayed a small underestimation of 0.9 beats per minute (bpm) and a limited capability to capture sudden HR changes because of the lower time resolution compared to that of PSG. The underestimation was smaller in N2, N3, and REM sleep (0.6-0.7 bpm) than in N1 sleep (1.2 bpm) and wakefulness (1.9 bpm), indicating a state-specific bias. Finally, Fitbit suggested a distribution of all sleep episode durations that was different from that derived from PSG and showed nonbiological discontinuities, indicating the potential limitations of the staging algorithm. CONCLUSIONS We conclude that by following careful data processing processes, the Fitbit Charge 2 can provide reasonably accurate mean values of sleep and HR estimates in shift workers under naturalistic conditions. Nevertheless, the generally wide limits of agreement hamper the precision of quantifying individual sleep episodes. The value of this consumer-grade multisensor wearable in terms of tackling clinical and research questions could be enhanced with open-source algorithms, raw data access, and the ability to blind participants to their own sleep data.
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.2196/preprints.26476
- OA Status
- gold
- Cited By
- 1
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4249497230
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4249497230Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/preprints.26476Digital Object Identifier
- Title
-
Validation of Fitbit Charge 2 Sleep and Heart Rate Estimates Against Polysomnographic Measures in Shift Workers: Naturalistic Study (Preprint)Work title
- Type
-
preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-12-14Full publication date if available
- Authors
-
Benjamin Stucky, Ian D. Clark, Yasmine Azza, Walter Karlen, Peter Achermann, Birgit Kleim, Hans‐Peter LandoltList of authors in order
- Landing page
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https://doi.org/10.2196/preprints.26476Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.2196/preprints.26476Direct OA link when available
- Concepts
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Polysomnography, Actigraphy, Sleep (system call), Sleep onset, Population, Wearable computer, Sleep onset latency, Medicine, Psychology, Statistics, Computer science, Circadian rhythm, Insomnia, Mathematics, Electroencephalography, Internal medicine, Psychiatry, Environmental health, Operating system, Embedded systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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