Daytime Sleep-Tracking Performance of Four Commercial Wearable Devices During Unrestricted Home Sleep

References

• Goldstein C. Current and future roles of consumer sleep technologies in sleep medicine. Sleep Med Clin. 2020;15(3):391–408. doi:10.1016/j.jsmc.2020.05.001
   PubMed Web of Science ®Google Scholar
• Baumert M, Cowie MR, Redline S, et al. Sleep characterization with smart wearable devices: a call for standardization and consensus recommendations. Sleep. 2022;45(12):zsac183. doi:10.1093/sleep/zsac183
   PubMed Web of Science ®Google Scholar
• de Zambotti M, Cellini N, Menghini L, Sarlo M, Baker FC. Sensors capabilities, performance, and use of consumer sleep technology. Sleep Med Clin. 2020;15(1):1–30. doi:10.1016/j.jsmc.2019.11.003
   PubMed Web of Science ®Google Scholar
• Lujan MR, Perez-Pozuelo I, Grandner MA. Past, present, and future of multisensory wearable technology to monitor sleep and circadian rhythms. Front Digit Health. 2021;3:721919. doi:10.3389/fdgth.2021.721919
   PubMedGoogle Scholar
• Khosla S, Deak MC, Gault D, et al. Consumer sleep technology: an American Academy of Sleep Medicine position statement. J Clin Sleep Med. 2018;14(5):877–880. doi:10.5664/jcsm.7128
   PubMed Web of Science ®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
• Schutte-Rodin S, Deak MC, Khosla S, et al. Evaluating consumer and clinical sleep technologies: an American Academy of Sleep Medicine update. J Clin Sleep Med. 2021;17(11):2275–2282. doi:10.5664/jcsm.9580
   PubMed Web of Science ®Google Scholar
• de Zambotti M, Menghini L, Grandner MA, et al. Rigorous performance evaluation (previously, “validation”) for informed use of new technologies for sleep health measurement. Sleep Health. 2022;8(3):263–269. doi:10.1016/j.sleh.2022.02.006
   PubMed Web of Science ®Google Scholar
• Grandner MA, Rosenberger ME. Chapter 12 - actigraphic sleep tracking and wearables: historical context, scientific applications and guidelines, limitations, and considerations for commercial sleep devices. In: Grandner MA, editor. Sleep and Health. Academic Press; 2019:147–157. doi:10.1016/B978-0-12-815373-4.00012-5
   Google Scholar
• Montgomery-Downs HE, Insana SP, Bond JA. Movement toward a novel activity monitoring device. Sleep Breath. 2012;16(3):913–917. doi:10.1007/s11325-011-0585-y
   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
• 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
• Lee XK, Chee NIYN, Ong JL, et al. Validation of a consumer sleep wearable device with actigraphy and polysomnography in adolescents across sleep opportunity manipulations. J Clin Sleep Med. 2019;15(9):1337–1346. doi:10.5664/jcsm.7932
   PubMed Web of Science ®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
• 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
• Chinoy ED, Cuellar JA, Jameson JT, Markwald RR. Performance of four commercial wearable sleep-tracking devices tested under unrestricted conditions at home in healthy young adults. Nat Sci Sleep. 2022;14:493–516. doi:10.2147/NSS.S348795
   PubMed Web of Science ®Google Scholar
• Grandner MA, Bromberg Z, Hadley A, et al. Performance of a multisensor smart ring to evaluate sleep: in-lab and home-based evaluation of generalized and personalized algorithms. Sleep. 2023;46(1):zsac152. doi:10.1093/sleep/zsac152
   PubMed Web of Science ®Google Scholar
• Ancoli-Israel S, Cole R, Alessi C, Chambers M, Moorcroft W, Pollak CP. The role of actigraphy in the study of sleep and circadian rhythms. Sleep. 2003;26(3):342–392. doi:10.1093/sleep/26.3.342
   PubMed Web of Science ®Google Scholar
• Lambrechtse P, Ziesenitz VC, Cohen A, van den Anker JN, Bos EJ. How reliable are commercially available trackers in detecting daytime sleep [letter to the editor]. Br J Clin Pharmacol. 2018;84(3):605–606. doi:10.1111/bcp.13475
   PubMed Web of Science ®Google Scholar
• Watson NF, Badr MS, Belenky G, et al. Recommended amount of sleep for a healthy adult: a joint consensus statement of the American Academy of Sleep Medicine and Sleep Research Society. Sleep. 2015;38(6):843–844. doi:10.5665/sleep.4716
   PubMed Web of Science ®Google Scholar
• Chinoy ED, Markwald RR. Use of technology for real-world sleep and circadian research. In: Encyclopedia of Sleep and Circadian Rhythms. 2nd ed. Elsevier; 2023:156–168. doi:10.1016/B978-0-12-822963-7.00200-0
   Google Scholar
• Carney CE, Buysse DJ, Ancoli-Israel S, et al. The consensus sleep diary: standardizing prospective sleep self-monitoring. Sleep. 2012;35(2):287–302. doi:10.5665/sleep.1642
   PubMed Web of Science ®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
• Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–310. doi:10.1016/S0140-6736(86)90837-8
   PubMed Web of Science ®Google Scholar
• Bakdash JZ, Marusich LR. Repeated measures correlation. Front Psychol. 2017;8:456. doi:10.3389/fpsyg.2017.00456
   PubMed Web of Science ®Google Scholar
• Polar Sleep Plus StagesTM FAQS. Available from: https://support.polar.com/en/sleep-plus-stages-faqs. Accessed February 2, 2023.
   Google Scholar
• Oura Nap Detection. Available from: https://support.ouraring.com/hc/en-us/articles/1500009653181-Nap-Detection. Accessed February 2, 2023.
   Google Scholar
• How do I track my sleep with my Fitbit device? Available from: https://help.fitbit.com/articles/en_US/Help_article/1314.htm. Accessed February 2, 2023.
   Google Scholar
• James L, James SM, Wilson M, et al. Sleep health and predicted cognitive effectiveness of nurses working 12-hour shifts: an observational study. Int J Nurs Stud. 2020;112:103667. doi:10.1016/j.ijnurstu.2020.103667
   PubMed Web of Science ®Google Scholar
• James L, Caruso CC, James S. Pilot test of NIOSH training for law enforcement on shift work and long work hours. J Occup Environ Med. 2022;64(7):599–606. doi:10.1097/JOM.0000000000002534
   PubMed Web of Science ®Google Scholar
• Erickson ML, Wang W, Counts J, et al. Field-based assessments of behavioral patterns during shiftwork in police academy trainees using wearable technology. J Biol Rhythms. 2022;37(3):260–271. doi:10.1177/07487304221087068
   PubMed Web of Science ®Google Scholar
• Sargent C, Lastella M, Romyn G, Versey N, Miller DJ, Roach GD. How well does a commercially available wearable device measure sleep in young athletes? Chronobiol Int. 2018;35(6):754–758. doi:10.1080/07420528.2018.1466800
   PubMed Web of Science ®Google Scholar
• Cook JD, Prairie ML, Plante DT. Ability of the multisensory jawbone UP3 to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: a comparison against polysomnography and actigraphy. J Clin Sleep Med. 2018;14(5):841–848. doi:10.5664/jcsm.7120
   PubMed Web of Science ®Google Scholar
• Miller DJ, Roach GD, Lastella M, et al. A validation study of a commercial wearable device to automatically detect and estimate sleep. Biosensors. 2021;11(6):185. doi:10.3390/bios11060185
   PubMedGoogle Scholar
• Devine JK, Schwartz LP, Choynowski J, Hursh SR. Expert demand for consumer sleep technology features and wearable devices: a case study. IoT. 2022;3(2):315–331. doi:10.3390/iot3020018
   Google Scholar
• Devine JK, Schwartz LP, Hursh SR. Technical, regulatory, economic, and trust issues preventing successful integration of sensors into the mainstream consumer wearables market. Sensors. 2022;22(7):2731. doi:10.3390/s22072731
   PubMed Web of Science ®Google Scholar
• Walch O, Huang Y, Forger D, Goldstein C. Sleep stage prediction with raw acceleration and photoplethysmography heart rate data derived from a consumer wearable device. Sleep. 2019;42(12):zsz180. doi:10.1093/sleep/zsz180
   PubMed Web of Science ®Google Scholar
• Cheng P, Walch O, Huang Y, et al. Predicting circadian misalignment with wearable technology: validation of wrist-worn actigraphy and photometry in night shift workers. Sleep. 2021;44(2):zsaa180. doi:10.1093/sleep/zsaa180
   PubMed Web of Science ®Google Scholar
• Huang Y, Mayer C, Cheng P, et al. Predicting circadian phase across populations: a comparison of mathematical models and wearable devices. Sleep. 2021;44(10):zsab126. doi:10.1093/sleep/zsab126
   PubMed Web of Science ®Google Scholar
• Kanady JC, Drummond SPA, Mednick SC. Actigraphic assessment of a polysomnographic-recorded nap: a validation study. J Sleep Res. 2011;20(1 Pt 2):214–222. doi:10.1111/j.1365-2869.2010.00858.x
   PubMed Web of Science ®Google Scholar
• Dunn J, Kidzinski L, Runge R, et al. Wearable sensors enable personalized predictions of clinical laboratory measurements. Nat Med. 2021;27(6):1105–1112. doi:10.1038/s41591-021-01339-0
   PubMed Web of Science ®Google Scholar
• Mason AE, Kasl P, Hartogensis W, et al. Metrics from wearable devices as candidate predictors of antibody response following vaccination against COVID-19: data from the second TemPredict study. Vaccines. 2022;10(2):264. doi:10.3390/vaccines10020264
   Web of Science ®Google Scholar
• Cheng P, Drake C. Shift work disorder. Neurol Clin. 2019;37(3):563–577. doi:10.1016/j.ncl.2019.03.003
   PubMed Web of Science ®Google Scholar
• Good CH, Brager AJ, Capaldi VF, Mysliwiec V. Sleep in the United States military. Neuropsychopharmacology. 2020;45(1):176–191. doi:10.1038/s41386-019-0431-7
   PubMed Web of Science ®Google Scholar
• Gurubhagavatula I, Barger LK, Barnes CM, et al. Guiding principles for determining work shift duration and addressing the effects of work shift duration on performance, safety, and health: guidance from the American Academy of Sleep Medicine and the Sleep Research Society. Sleep. 2021;44(11):zsab161. doi:10.1093/sleep/zsab161
   PubMed Web of Science ®Google Scholar
• Colvonen PJ, DeYoung PN, Bosompra NOA, Owens RL. Limiting racial disparities and bias for wearable devices in health science research. Sleep. 2020;43(10):zsaa159. doi:10.1093/sleep/zsaa159
   PubMed Web of Science ®Google Scholar