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Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
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Published on: August 8, 2019

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Fatigue and Sleep Assessment using Digital Sleep Trackers: Insights from a Multi-Device Pilot Study

Luan Chen, Xujun Ma, Meenakshi Chatterjee

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |September 10, 2022
    PubMed

    Abstract:

    For the patient community with neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID), fatigue and sleep disturbances stand out as two of the most common and disabling symptoms, which mightily impair patient's quality of life. Traditional questionnaire-oriented approaches to reflect such symptoms suffer from recall bias and poor sensitivity to change. By virtue of multiple sensing modalities at home, IDEA-FAST project aims to identify novel digital endpoints of fatigue and sleep disturbances, that are objective, reliable and sensitive to change. This article presents and discusses results from a pilot study of IDEA-FAST to evaluate the feasibility of capturing sleep and fatigue measures from three sleep trackers. Data collected from 143 participants (age range: 21-82) across 6 disease groups and healthy cohort for a period of 9 months, were investigated using our proposed sensor analytical pipeline. The overall performance reveals that the median coverage rate of sleep trackers ranged from 48.3% to 76.9%. Furthermore, the digital measures obtained from each device, indicated a higher association with sleep related patient reported outcomes (PROs) than fatigue related ones, when taking all participants into account.

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