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    Home»Sleep Health»Standardising wearable sleep data: New Fundamental Sleep Measures Specification defines a common language for sleep tracking for clinical, research and public health use
    Sleep Health

    Standardising wearable sleep data: New Fundamental Sleep Measures Specification defines a common language for sleep tracking for clinical, research and public health use

    HealthJustfine TeamBy HealthJustfine TeamOctober 15, 2026No Comments7 Mins Read
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    Standardising wearable sleep data: New Fundamental Sleep Measures Specification defines a common language for sleep tracking for clinical, research and public health use
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    A team of sleep scientists, clinicians, and engineers from academia and industry proposes common definitions and data standards for a core set of Fundamental Sleep Measures (FSMs) generated by consumer health trackers, paving the way for more meaningful clinical care, research and public health

    SINGAPORE and ROCHESTER, Minn., Oct. 13, 2026 /PRNewswire-PRWeb/ — Consumer wearables have transformed the ability to monitor sleep over weeks, months and even years. Yet a surprisingly basic problem remains: two devices may report a measure called “total sleep time” while defining, calculating or quality-controlling it differently

    A multinational, multidisciplinary team of sleep scientists, clinicians, and engineers from academia and industry convened by World Sleep Society has developed a specification designed to address this problem. Published in Sleep Medicine, the proposed framework establishes common definitions and data standards for a core set of Fundamental Sleep Measures (FSMs) generated by consumer health trackers.

    The goal is not to make every wearable work in the same way. Manufacturers would remain free to choose their sensors, algorithms, machine-learning approaches, and consumer-facing interfaces. Instead, the specification standardises what key sleep measurements mean when they are exported for clinical, research or public-health use

    The Same Name Should Mean the Same Thing

    Measures such as total sleep time, sleep efficiency, wake after sleep onset and sleep regularity are already widely reported by wearable devices. However, identically named measures may not refer to the same construct across manufacturers, limiting their comparability and usefulness in healthcare and research

    The new specification addresses this by defining a common semantic framework for fundamental measures including sleep onset and offset, the main sleep period, sleep duration, wake after sleep onset, sleep regularity, 24-hour sleep including naps, and subjective sleep satisfaction. It also introduces explicit rules for handling missing or uncertain data

    Professor Michael Chee, Director at the Centre for Sleep and Cognition, NUS Yong Loo Lin School of Medicine (NUS Medicine) who led the team, said, “People naturally assume that a measurement called ‘Total Sleep Time’ means the same thing regardless of which device produced it. In reality, manufacturers often use different definitions, algorithms, and quality controls.”

    “Without common definitions, it is difficult for clinicians, researchers and healthcare systems to know whether they are comparing like with like,” added Professor Sean Drummond, School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, co-chair of the specification team

    From Interesting Data to Useful Health Information

    Wearables have a major advantage over traditional sleep assessments: they can characterise sleep repeatedly in everyday life and over long periods. But exploiting that information clinically requires more than accurate sensors

    Healthcare systems depend on standardised measurements. Blood pressure, laboratory tests and other clinical measurements are useful partly because clinicians understand what a reported value represents. Wearable sleep data currently lack an equivalent level of consistency. This becomes particularly important as consumer-generated health information begins to enter electronic health records (EHRs).

    The specification therefore focuses on the underlying data architecture required for interoperability. It defines not only sleep measures but also their metadata, provenance, quality indicators, time boundaries, and rules for dealing with incomplete recordings. Its objective is to allow data produced by different devices to be interpreted consistently by EHRs, research databases and population-health systems.

    Focusing on Measures People Can Understand—and Act Upon

    The framework deliberately emphasises fundamental and interpretable aspects of sleep rather than proprietary scores or detailed estimates of sleep stages

    This distinction matters clinically. A person can take practical steps to provide adequate opportunity for sleep, adjust when they attempt to sleep, or establish a more regular schedule. By contrast, consumers have much less direct control over proprietary measures such as a “deep sleep score,” whose definitions and algorithms can vary among devices

    The specification also distinguishes behavioural intention from physiology. A person’s decision to try to sleep is not the same thing as the physiological onset of sleep, and the framework requires those concepts to be represented separately

    Similarly, it recommends replacing ambiguous terminology where necessary. Rather than using “Sleep Efficiency” when a wearable cannot independently establish that a person was actually in bed attempting to sleep, the specification defines a reproducible “Sleep Percentage” based on sleep occurring between physiological sleep onset and offset

    Standards Without Suppressing Innovation

    An important principle of the project is that interoperability should not require manufacturers to disclose proprietary algorithms or build identical products

    The specification does not prescribe which sensors should be used, how algorithms should be constructed or made public, how sleep stages should be classified, or what manufacturers should display in their apps. Instead, it establishes common backend meanings for a minimum set of measures. In other words, manufacturers can continue to compete on hardware, algorithms, design and user experience while still communicating fundamental sleep information in a common language.

    Built Jointly by Academic, Clinical and Industry Experts

    The specification, developed by a 16-member international team of academic scientists working with industry counterparts, built consensus on multiple complex issues over months of iterative discussions

    The cooperation of industry scientists from five companies that compete in the marketplace is unprecedented in this field, and was invaluable in ensuring the specification is not merely an academic exercise but a practical framework that can be readily incorporated into products

    “The collaboration demonstrates the value of the World Sleep Society mission, convening diverse stakeholders across sleep science and medicine to turn emerging challenges into opportunities,” noted Allan O’Bryan, Executive Director of the World Sleep Society

    Building the Infrastructure for Longitudinal Sleep Health

    The authors see standardisation as an important step toward a larger goal: moving wearable sleep information from isolated proprietary ecosystems toward data that can be meaningfully used across healthcare and public-health systems

    Long-term wearable data could eventually allow clinicians to consider not simply how someone slept last night, but whether they routinely obtain adequate sleep, maintain a stable schedule, or show sustained changes in sleep patterns alongside changes in health. For such applications to become scientifically credible, however, a basic requirement comes first: everyone must mean the same thing when they report the same sleep measure.

    “Wearables have given us an unprecedented ability to observe sleep in everyday life. Standardisation is what can turn those observations into information that clinicians, researchers and health systems can reliably understand and use,” Chee concluded

    About National University of Singapore (NUS)

    The National University of Singapore (NUS) is Singapore’s flagship university, which offers a global approach to education, research, and entrepreneurship, with a focus on Asian perspectives and expertise. We have 15 colleges, faculties, and schools across three campuses in Singapore, with more than 40,000 students from 100 countries enriching our vibrant and diverse campus community. We have also established around 15 NUS Overseas Colleges entrepreneurial hubs around the world.

    For more information on NUS, please visit www.nus.edu.sg

    About the NUS Yong Loo Lin School of Medicine (NUS Medicine)

    The NUS Yong Loo Lin School of Medicine is Singapore’s first and largest medical school. Our enduring mission centres on nurturing highly competent, values-driven, and inspired healthcare professionals to transform the practice of medicine and improve health around the world

    For more information about NUS Medicine, please visit https://medicine.nus.edu.sg/

    About World Sleep Society

    World Sleep Society is a professional association of sleep researchers and clinicians whose mission is to convene the world of sleep medicine science, practice and advocacy. World Sleep Society operates research, educational, and advocacy programs for the international professional sleep community, including the biennial World Sleep Congress, which hosts the largest live scientific program in sleep. The next World Sleep Congress is in Montreal, Canada, over September 10 – 15, 2027.

    Learn more at worldsleepsociety.org

    Media Contact

    Tyler RINGSTAD, World Sleep Society, 1 5073160084, [email protected], worldsleepsociety.org

    Shaun YEE, Yong Loo Lin School of Medicine, National University of Singapore, [email protected], www.nus.edu.sg/

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