Assessment of Fitbit Charge 4 for sleep stage and heart rate monitoring against polysomnography and during home monitoring in Huntington's disease

Doheny, Emer P., Renerts, Klavs, Braun, Andreas, Werth, Esther, Baumann, Christian, Baumgartner`, Philipp, Morgan-Jones, Philippa, Busse-Morris, Monica ORCID: https://orcid.org/0000-0002-5331-5909, Lowery, Madeleine M. and Jung, Hans H. 2024. Assessment of Fitbit Charge 4 for sleep stage and heart rate monitoring against polysomnography and during home monitoring in Huntington's disease. Journal of Clinical Sleep Medicine 20 (7) , pp. 1163-1171. 10.5664/jcsm.11098

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Abstract

Study Objectives: Wearable devices, monitoring sleep stages and heart rate (HR), bring the potential for longitudinal sleep monitoring in patients with neurodegenerative diseases. Sleep quality reduces with disease progression in Huntington’s disease (HD). However, the involuntary movements characteristic of HD may affect the accuracy of wrist-worn devices. This study compares sleep stage and heart rate data from the Fitbit Charge 4 (FB) against polysomnography (PSG) in participants with HD. Methods: Ten participants with manifest HD wore a FB during overnight hospital-based PSG, and for nine of these participants continued to wear the FB for seven nights at home. Sleep stages (30s epochs) and minute-by-minute HR were extracted and compared against PSG data. Results: FB-estimated total sleep and wake times, and sleep stage times were in good agreement with PSG, with intra-class correlations 0.79-0.96. However, poor agreement was observed for Wake After Sleep Onset, and the number of awakenings. FB detected wake with 68.6±15.5% sensitivity and 93.7±2.5% specificity, rapid eye movement (REM) sleep with high sensitivity and specificity (78.7±31.9%, 95.6±2.3%), and deep sleep with lower sensitivity but high specificity (56.4±28.8%, 95.0±4.8%). FB HR was strongly correlated with PSG, and the mean absolute error between FB and PSG HR data was 1.16 ± 0.42 bpm. At home, longer sleep and shorter wake times were observed compared to hospital data, while percentage sleep stage times were consistent with hospital data. Conclusions: Results suggest the potential for long-term monitoring of sleep patterns using wrist-worn wearable devices as part of symptom management in HD.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering Medicine Centre for Trials Research (CNTRR)
Publisher:	American Academy of Sleep Medicine
ISSN:	1550-9389
Funders:	Alzheimer's Society, Secretary of State for Health and Social Care, Health and Care Research Wales, Public Health Agency Northern Ireland, Jacques and Gloria Gossweiler Foundation, Bundesministerium für Bildung und Forschung, Narodowe Centrum Badań i Rozwo, Swiss National Science Foundation, Health Research Board
Date of First Compliant Deposit:	5 March 2024
Date of Acceptance:	20 February 2024
Last Modified:	08 Nov 2024 08:30
URI:	https://orca.cardiff.ac.uk/id/eprint/166895

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