Computational Sleep Behavior Analysis: A Survey

Sarah Fallmann, Liming (Luke) Chen

    Research output: Contribution to journalArticlepeer-review

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    Sleep is a key marker of health, as it can either be a cause or a consequence. It is
    traditionally studied in clinical environments using dedicated medical devices. Recent technological developments, e.g., in sensing and data analysis, have led to new approaches for sleep monitoring and assessment, which are attracting increasing attention in the emerging domain of personalized smart healthcare. Nevertheless, a high-level overview of technology-enabled research on sleep that can inform related communities of the latest developments is lacking. In this paper, we present a comprehensive review to examine the current status of various aspects of technology-based sleep research. We first characterize sleep behavior and key areas of sleep assessment, and we introduce a general review of the methodologies used in this domain. We review the major technological methods and trends associated with sleep monitoring, data collection and sleep behavior analysis, from which strengths and weaknesses are highlighted. Finally, we also discuss challenges and promising directions for future research.
    Original languageEnglish
    Number of pages17
    JournalIEEE Access
    Publication statusAccepted/In press - 20 Sept 2019


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