Rigorous performance evaluation (previously, “validation”) for informed use of new technologies for sleep health measurement

Massimiliano de Zambotti, Luca Menghini, Michael A. Grandner, Susan Redline, Ying Zhang, Meredith L. Wallace, Orfeu M. Buxton

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


New sleep technologies have become pervasive in the consumer space, and are becoming highly common in research and clinical sleep settings. The rapid, widespread use of largely unregulated and unstandardized technology has enabled the quantification of many different facets of sleep health, driving scientific discovery. As sleep scientists, it is our responsibility to inform principles and practices for proper evaluation of any new technology used in the clinical and research settings, and by consumers. A current lack of standardized methods for evaluating technology performance challenges the rigor of our scientific methods for accurate representation of the sleep health facets of interest. This special article describes the rationale and priorities of an interdisciplinary effort for rigorous, standardized, and rapid performance evaluation (previously, “validation”) of new sleep and sleep disorders related technologies of all kinds (eg, devices or algorithms), including an associated article template for a new initiative for publication in Sleep Health of empirical studies systematically evaluating the performance of new sleep technologies. A structured article type should streamline manuscript development and enable more rapid writing, review, and publication. The goal is to promote rapid and rigorous evaluation and dissemination of new sleep technology, to enhance sleep research integrity, and to standardize terminology used in Rigorous Performance Evaluation papers to prevent misinterpretation while facilitating comparisons across technologies.

Original languageEnglish (US)
Pages (from-to)263-269
Number of pages7
JournalSleep Health
Issue number3
StatePublished - Jun 2022


  • Actigraphy
  • Algorithms
  • Machine learning
  • Performance evaluations
  • Sensors
  • Wearables

ASJC Scopus subject areas

  • Health(social science)
  • Neuropsychology and Physiological Psychology
  • Social Sciences (miscellaneous)
  • Behavioral Neuroscience


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