Validation of Fitbit Inspire 2^TM Against Polysomnography in Adults Considering Adaptation for Use

References

• Cappuccio FP, Cooper D, D’Elia L, Strazzullo P, Miller MA. Sleep duration predicts cardiovascular outcomes: a systematic review and meta-analysis of prospective studies. Eur Heart J. 2011;32(12):1484–1492. doi:10.1093/eurheartj/ehr007
   PubMed Web of Science ®Google Scholar
• Xie J, Li Y, Zhang Y, et al. Sleep duration and metabolic syndrome: an updated systematic review and meta-analysis. Sleep Med Rev. 2021;59:101451. doi:10.1016/j.smrv.2021.101451
   PubMed Web of Science ®Google Scholar
• Shin D, Hur J, Cho KH, Cho EH. Trends of self-reported sleep duration in Korean adults: results from the Korea National Health and Nutrition Examination Survey 2007–2015. Sleep Med. 2018;52:103–106. doi:10.1016/j.sleep.2018.08.008
   PubMed Web of Science ®Google Scholar
• National Health Insurance Service. Useful Health Life Statistics Information to Know [Internet]. Wonju: National Health Insurance Sevice; 2021. Available from: https://www.nhis.or.kr/nhis/together/wbhaec06700m01.do?mode=view&articleNo=10811517. Accessed February 21, 2023.
   Google Scholar
• Lee YJ, Kim DJ, Lee H. A study on sleep-wake assessment for substantiation of sleep products. Sleep Med Psychophysiol. 2020;27(2):51–55.
   Google Scholar
• Depner CM, Cheng PC, Devine JK, et al. Wearable technologies for developing sleep and circadian biomarkers: a summary of workshop discussions. Sleep. 2020;43(2):zsz254. doi:10.1093/sleep/zsz254
   PubMed Web of Science ®Google Scholar
• Van de Water AT, Holmes A, Hurley DA. Objective measurements of sleep for non-laboratory settings as alternatives to polysomnography--a systematic review. J Sleep Res. 2011;20(1 Pt 2):183–200. doi:10.1111/j.1365-2869.2009.00814.x
   PubMed Web of Science ®Google Scholar
• FDA. Device software functions including mobile medical applications U.S. food & drug administration website; 2022. Available from: https://www.fda.gov/medical-devices/digital-health-center-excellence/device-software-functions-including-mobile-medical-applications. Accessed September 28, 2022.
   Google Scholar
• Fitbit. What should I know about sleep stages? [homepage on the Internet]. Available from: https://help.fitbit.com/articles/en_US/Help_article/2163. Accessed July 26, 2022.
   Google Scholar
• Cook JD, Prairie ML, Plante DT. Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: a comparison against polysomnography and wrist-worn actigraphy. J Affect Disord. 2017;217:299–305. doi:10.1016/j.jad.2017.04.030
   PubMed Web of Science ®Google Scholar
• Moreno-Pino F, Porras-Segovia A, López-Esteban P, Artés A, Baca-García E. Validation of fitbit charge 2 and fitbit alta HR against polysomnography for assessing sleep in adults with obstructive sleep apnea. J Clin Sleep Med. 2019;15(11):1645–1653. doi:10.5664/jcsm.8032
   PubMed Web of Science ®Google Scholar
• Scott H, Lack L, Lovato N. A systematic review of the accuracy of sleep wearable devices for estimating sleep onset. Sleep Med Rev. 2020;49:101227. doi:10.1016/j.smrv.2019.101227
   PubMed Web of Science ®Google Scholar
• Haghayegh S, Khoshnevis S, Smolensky MH, Diller KR, Castriotta RJ. Accuracy of wristband fitbit models in assessing sleep: systematic review and meta-analysis. J Med Internet Res. 2019;21(11):e16273. doi:10.2196/16273
   PubMed Web of Science ®Google Scholar
• Munos B, Baker PC, Bot BM, et al. Mobile health: the power of wearables, sensors, and apps to transform clinical trials. Ann N Y Acad Sci. 2016;1375(1):3–18. doi:10.1111/nyas.13117
   PubMedGoogle Scholar
• Cook JD, Eftekari SC, Dallmann E, Sippy M, Plante DT. Ability of the Fitbit Alta HR to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: a comparison against polysomnography. J Sleep Res. 2019;28(4):e12789. doi:10.1111/jsr.12789
   PubMed Web of Science ®Google Scholar
• Lunsford-Avery JR, Keller C, Kollins SH, Krystal AD, Jackson L, Engelhard MM. Feasibility and acceptability of wearable sleep electroencephalogram device use in adolescents: observational study. JMIR Mhealth Uhealth. 2020;8(10):e20590. doi:10.2196/20590
   PubMed Web of Science ®Google Scholar
• Meltzer LJ, Hiruma LS, Avis K, Montgomery-Downs H, Valentin J. Comparison of a commercial accelerometer with polysomnography and actigraphy in children and adolescents. Sleep. 2015;38(8):1323–1330. doi:10.5665/sleep.4918
   PubMed Web of Science ®Google Scholar
• de Zambotti M, Baker FC, Willoughby AR, et al. Measures of sleep and cardiac functioning during sleep using a multi-sensory commercially-available wristband in adolescents. Physiol Behav. 2016;158:143–149. doi:10.1016/j.physbeh.2016.03.006
   PubMed Web of Science ®Google Scholar
• Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001;2(4):297–307. doi:10.1016/S1389-9457(00)00065-4
   PubMed Web of Science ®Google Scholar
• Hori T, Sugita Y, Koga E, Shirakawa S, Inoue K. Proposed supplements and amendments to ‘A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects’, the Rechtschaffen & Kales (1968) standard. Psychiatry Clin Neurosci. 2001;55:305–310.
   PubMed Web of Science ®Google Scholar
• Sleep API variable: sleep [homepage on the Internet]. Available from: https://dev.fitbit.com/. Accessed July 26, 2022.
   Google Scholar
• Menghini L, Cellini N, Goldstone A, Baker FC, de Zambotti M. A standardized framework for testing the performance of sleep-tracking technology: step-by-step guidelines and open-source code. Sleep. 2021;44(2):zsaa170. doi:10.1093/sleep/zsaa170
   PubMed Web of Science ®Google Scholar
• Kosmadopoulos A, Sargent C, Darwent D, Zhou X, Roach GD. Alternatives to polysomnography (PSG): a validation of wrist actigraphy and a partial-PSG system. Behav Res Methods. 2014;46(4):1032–1041. doi:10.3758/s13428-013-0438-7
   PubMed Web of Science ®Google Scholar
• Peters B. Why WASO has a negative effect on sleep quality; 2022. Available from: https://www.verywellhealth.com/understanding-and-treating-waso-3015394. Accessed February 21, 2023.
   Google Scholar
• Scott H, Lovato N, Lack L. The development and accuracy of the THIM wearable device for estimating sleep and wakefulness. Nat Sci Sleep. 2021;13:39. doi:10.2147/NSS.S287048
   PubMed Web of Science ®Google Scholar
• Kim E-J, Ahn Y-M, Shin H-B, Kim J-W. Detrended fluctuation analysis of sleep electroencephalogram between obstructive sleep apnea syndrome and normal children. Sleep Med Psychophysiol. 2010;17(1):41–49.
   Google Scholar
• Kahawage P, Jumabhoy R, Hamill K, de Zambotti M, Drummond SPA. Validity, potential clinical utility, and comparison of consumer and research-grade activity trackers in Insomnia Disorder I: in-lab validation against polysomnography. J Sleep Res. 2020;29(1):e12931. doi:10.1111/jsr.12931
   PubMed Web of Science ®Google Scholar
• Mantua J, Gravel N, Spencer RM. Reliability of sleep measures from four personal health monitoring devices compared to research-based actigraphy and polysomnography. Sensors. 2016;16(5):646. doi:10.3390/s16050646
   PubMed Web of Science ®Google Scholar
• Chinoy ED, Cuellar JA, Huwa KE, et al. Performance of seven consumer sleep-tracking devices compared with polysomnography. Sleep. 2021;44(5):zsaa291. doi:10.1093/sleep/zsaa291
   PubMed Web of Science ®Google Scholar
• Le Bon O, Staner L, Hoffmann G, et al. The first-night effect may last more than one night. J Psychiatric Res. 2001;35(3):165–172. doi:10.1016/S0022-3956(01)00019-X
   PubMed Web of Science ®Google Scholar
• Newell J, Mairesse O, Verbanck P, Neu D. Is a one-night stay in the lab really enough to conclude? First-night effect and night-to-night variability in polysomnographic recordings among different clinical population samples. Psychiatr Res. 2012;200(2–3):795–801. doi:10.1016/j.psychres.2012.07.045
   PubMed Web of Science ®Google Scholar
• Stucky B, Clark I, Azza Y, et al. Validation of Fitbit Charge 2 sleep and heart rate estimates against polysomnographic measures in shift workers: naturalistic study. J Med Internet Res. 2021;23(10):e26476. doi:10.2196/26476
   PubMed Web of Science ®Google Scholar
• Kawasaki Y, Kasai T, Sakurama Y, et al. Evaluation of sleep parameters and sleep staging (slow wave sleep) in athletes by fitbit alta HR, a consumer sleep tracking device. Nat Sci Sleep. 2022;14:819–827. doi:10.2147/NSS.S351274
   PubMed Web of Science ®Google Scholar
• Leung W, Case L, Sung MC, Jung J. A meta-analysis of Fitbit devices: same company, different models, different validity evidence. J Med Eng Technol. 2022;46(2):102–115. doi:10.1080/03091902.2021.2006350
   PubMedGoogle Scholar