Email this article 
Comparison of somnological parameters obtained using sports watches POLAR VANTAGE V and polysomnography method
- Authors: Vjotosh A.N.1,2, Petrov A.B.2, Djubenkov S.A.2, Tikhomirova O.V.3
-
Affiliations:
- Sechenov Institute of Evolutionary Physiology and Biochemistry of the RAS
- Lesgaft National State University of Physical Education, Sport and Health
- Nikiforov Russian Center of Emergency and Radiation Medicine
- Issue: Vol 51, No 2 (2025)
- Pages: 131-136
- Section: Articles
- URL: https://journals.rcsi.science/0131-1646/article/view/304848
- ID: 304848
Cite item
Open Access
Access granted
Subscription Access
Abstract
Synchronous registration of sleep parameters in practically healthy young womens was carried out using polysomnography and by recording the rhythmocardiographic activity of the sleeping body using a Polar Vantage V sports watch. The data obtained were compared in pairs, using the Spearman rank correlation method and by epoch-by-epoch comparison of sleep phase coincidence indicators. A high degree of correspondence was revealed with the total duration of sleep, time spent in bed, sleep efficiency values and the total duration of short-term awakenings recorded by the two above-mentioned methods. The mode of epoch-by-epoch comparison of the periods of coincidence of the Rem phases, as well as the N2 and N3 phases during polysomnographic and rhythmocardiographic registration, brought results not exceeding 60%.
About the authors
A. N. Vjotosh
Sechenov Institute of Evolutionary Physiology and Biochemistry of the RAS; Lesgaft National State University of Physical Education, Sport and Health
Email: vjotnn@yahoo.com
St. Peterburg, Russia; St. Peterburg, Russia
A. B. Petrov
Lesgaft National State University of Physical Education, Sport and Health
Email: vjotnn@yahoo.com
St. Peterburg, Russia
S. A. Djubenkov
Lesgaft National State University of Physical Education, Sport and Health
Email: vjotnn@yahoo.com
St. Peterburg, Russia
O. V. Tikhomirova
Nikiforov Russian Center of Emergency and Radiation Medicine
Author for correspondence.
Email: vjotnn@yahoo.com
St. Peterburg, Russia
References
- Vein A.M. [Waking ang sleep]. M.: Nauka, 1970. 125 p.
- Stone J.D., Rentz L.E., Forsley J. et al. Evaluations of commercial sleep tehnologies for objective monitoring during routine sleeping conditions // Nat. Sci. Sleep. 2020. V. 12. P. 821.
- Karmanova I.G., Oganesyan G.A. [Physiology and Pathology of the Sleep-Wake Cycle. Evolutionary Aspects]. М.: Nauka, 1994. 200 p.
- Kovalzon V.M. [Basics of Somnology]. M.: “Laboratoriya znanii”, 2012. 239 p.
- Vjotosh A.N., Petrov A.B., Kotova A.S., Tikhomiro-va O.V. Possibilities and Limitations on Using Sleep Cycle Smartphone Apps for Sleep Analysis in Sports Practice // Human Physiology. 2023. V. 49. № 6. P. 663.
- Ameen M.S., Cheung L.M., Hauser T. et al. About the accuracy and problems of consumer devices in the assessment of sleep // Sensors. 2019. V. 19. № 19. P. 4160.
- Chinoy E.D., Cuellar J.A., Jameson J.T., Mark- wald R.R. Performance of four commercial wearable sleep-tracking devices tested under unrestricted conditions at home in healthy young adults // Nat. Sci. Sleep. 2022. V. 14. P. 493.
- Miller D.J., Sargent C., Roach G.D. A validation of six wearable devices for estimating sleep, heart rate and heart rate variability in healthy adults // Sensors. 2022. V. 22. № 16. P. 6317.
- Kushida C.F., Littner M.R., Morgenthaler T. et al. Practice parameters for the indications for polysomnography and related procedures: An update for 2005 // Sleep. 2005. V. 28. № 4. P. 499.
- Lee J.-M., Byun W., Keill A. et al. Comparison of wearable trackers’ ability to estimate sleep // Int. J. Envir. Res. Public Health. 2018. V. 15. № 6. P. 1265.
- Chinoy E.D., Cuellar J.A., Jameson J.T., Mark- wald R.R. Daytime sleep-tracking performance of four commercial wearable devices during unrestricted home sleep // Nat. Sci. Sleep. 2023. V. 15. P. 151.
- Radha M., Fonseca P., Moreau A. et al. Sleep stage classification from heart-rate variability using long short-term memory neural networks // Sci. Rep. 2019. V. 9. № 1. P. 14149.
- Li D., Ruan Y., Zheng F. et al. Fast sleep stage classification using cascaded support vector machines with single-channel EEG signals // Sensors. 2022. V. 22. № 24. P. 9914.
Supplementary files
