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BRIEF RESEARCH REPORT article

Front. Sleep
Sec. Precision Sleep Medicine
Volume 3 - 2024 | doi: 10.3389/frsle.2024.1481878

Performance of the Verily Study Watch for Measuring Sleep Compared to Polysomnography

Provisionally accepted
Sohrab Saeb Sohrab Saeb 1*Benjamin W Nelson Benjamin W Nelson 1,2Poulami Barman Poulami Barman 1Nishant Verma Nishant Verma 1Hannah Allen Hannah Allen 1Massimiliano de Zambotti Massimiliano de Zambotti 3Fiona C Baker Fiona C Baker 3Nicole Arra Nicole Arra 3Niranjan Sridhar Niranjan Sridhar 3Shannon Sullivan Shannon Sullivan 1,4Scooter Plowman Scooter Plowman 1Erin Rainaldi Erin Rainaldi 1Ritu Kapur Ritu Kapur 1,5Sooyoon Shin Sooyoon Shin 1
  • 1 Verily Life Sciences LLC, Mountain View, United States
  • 2 Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
  • 3 SRI International, Menlo Park, California, United States
  • 4 Division of Pulmonary Medicine, Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, United States
  • 5 Department of Neurology, Radboud University Medical Centre, Nijmegen, Gelderland, Netherlands

The final, formatted version of the article will be published soon.

    Introduction: This study evaluated the performance of a wrist-worn wearable, Verily Study Watch (VSW), in detecting key sleep measures against polysomnography (PSG). Methods: We collected data from 41 adults without obstructive sleep apnea or insomnia during a single overnight laboratory visit. We evaluated epoch-by-epoch performance for sleep versus wake classification, sleep stage classification and duration, total sleep time (TST), wake after sleep onset (WASO), sleep onset latency (SOL), sleep efficiency (SE), and number of awakenings (NAWK). Performance metrics included sensitivity, specificity, Cohen’s kappa, and Bland-Altman analyses. Results: Sensitivity and specificity (95% CIs) of sleep versus wake classification were 0.97 (0.96, 0.98) and 0.70 (0.66, 0.74), respectively. Cohen’s kappa (95% CI) for 4-class stage detection was 0.64 (0.18, 0.82). Most VSW sleep measures had proportional bias. The mean bias values (95% CI) were 14.0 minutes (5.55, 23.20) for TST, -13.1 minutes (-21.33, -6.21) for WASO, 2.97% (1.25, 4.84) for SE, -1.34 minutes (-7.29, 4.81) for SOL, 1.91 minutes (-8.28, 11.98) for light sleep duration, 5.24 minutes (-3.35, 14.13) for deep sleep duration, and 6.39 minutes (-0.68, 13.18) for REM sleep duration. Mean and median NAWK count differences (95% CI) were 0.05 (-0.42, 0.53) and 0.0 (0.0, 0.0), respectively. Discussion: Results support applying the VSW to track overnight sleep measures in free-living settings. Registered at clinicaltrials.gov (NCT05276362). 

    Keywords: sleep-wake detection, sleep stage, digital health measures, Polysomnography, Freeliving, sleep detection accuracy

    Received: 16 Aug 2024; Accepted: 20 Nov 2024.

    Copyright: © 2024 Saeb, Nelson, Barman, Verma, Allen, de Zambotti, Baker, Arra, Sridhar, Sullivan, Plowman, Rainaldi, Kapur and Shin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Sohrab Saeb, Verily Life Sciences LLC, Mountain View, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.