The site of the Media Sphera Publishers contains materials intended solely for healthcare professionals.
By closing this message, you confirm that you are a certified medical professional or a student of a medical educational institution.

Login
EN
+7 (495) 482-4118
+7 (495) 482-0604
+8 800 250-18-12
  • (toll-free number for subscriptions)
    Mon-Fri from 10 a.m. to 6 p.m.

  • © 1998-2025
+7 (495) 482-43-29
EN
All journals
Journal
Year
Year
Search result: 0

Manaenkov A.E.

Institute of Higher Nervous Activity and Neurophysiology;
Lomonosov Moscow State University

Prokhorenko N.O.

Institute of Higher Nervous Activity and Neurophysiology;
Pirogov Russian National Research Medical University

Tkachenko O.N.

Institute of Higher Nervous Activity and Neurophysiology

Sveshnikov D.S.

Medical Institute of Peoples’ Friendship University of Russia

Dorokhov V.B.

Institute of Higher Nervous Activity and Neurophysiology

Correlation of the Karolinska sleepiness scale with performance variables of the monotonous bimanual psychomotor test

Authors:

Manaenkov A.E., Prokhorenko N.O., Tkachenko O.N., Sveshnikov D.S., Dorokhov V.B.

More about the authors

Journal: S.S. Korsakov Journal of Neurology and Psychiatry. 2023;123(5‑2): 28‑34

DOI: 10.17116/jnevro202312305228

Views: 2398

Downloaded: 37

Download PDF (RU)
Contact the author
Table of contents

CORRELATION OF THE KAROLINSKA SLEEPINESS SCALE WITH PERFORMANCE VARIABLES OF THE MONOTONOUS BIMANUAL PSYCHOMOTOR TEST
CORRELATION OF THE KAROLINSKA SLEEPINESS SCALE WITH PERFORMANCE VARIABLES OF THE MONOTONOUS BIMANUAL PSYCHOMOTOR TEST

To cite this article:

Manaenkov AE, Prokhorenko NO, Tkachenko ON, Sveshnikov DS, Dorokhov VB. Correlation of the Karolinska sleepiness scale with performance variables of the monotonous bimanual psychomotor test. S.S. Korsakov Journal of Neurology and Psychiatry. 2023;123(5‑2):28‑34. (In Russ.)
https://doi.org/10.17116/jnevro202312305228

Подписка 2025-2 (S.S. Korsakov Journal of Neurology and Psychiatry (special issues))
 
 
МСФ на ЯМ
Close metadata
Recommended articles:
To study the effe­ctiveness and impact on the quality of life of patients with subclinical and clinically pronounced anxiety diso­rder of a mobile application in combination with Adaptol therapy. S.S. Korsakov Journal of Neurology and Psychiatry. 2024;(7):98-105
App-based first aid learning: what applications do we have now?. Russian Journal of Anesthesiology and Reanimatology. 2024;(6):89-103
Predictors of Enga­gement and Active participation of Patients with Unco­ntrolled Hype­rtension in the Tele­health Surveillance Program. Russian Journal of Preventive Medi­cine. 2024;(12):37-43
Impairments in sustained atte­ntion and the effi­ciency of psychomotor acti­vity during episodes of spontaneous awakening from daytime sleep. S.S. Korsakov Journal of Neurology and Psychiatry. 2025;(2):101-106
The effect of a gami­fication on healthy indi­viduals’ motor acti­vity. Russian Journal of Preventive Medi­cine. 2025;(4):111-116

OBJECTIVE

To assess the objectivity of measuring the level of sleepiness in the subjects using a monotonous psychomotor bimanual tapping test developed by us, performed on mobile devices running Android OS.

MATERIAL AND METHODS

Four hundred and ninety-four hour-long experiments with the performance of a psychomotor test were conducted on 102 students. Using the method of mixed linear models, correlations between the levels of sleepiness according to the Karolinska Sleepiness Scale (KSS) and the Epworth Sleepiness Scale (ESS) and the behavioral indicators of the test were evaluated.

RESULTS

Statistically significant correlations between the increase in KSS scores and such indicators as a decrease in the total number of button taps and an increase in the frequency of «microsleep» episodes are shown. Statistically significant correlations of ESS score characteristics with the behavioral indicators of the test were not found.

CONCLUSION

A large statistical material shows a reliable correlation of the parameters of the psychomotor test with the level of sleepiness on the Karolinska scale, which allows using the mobile application developed by us to determine the current level of sleepiness /alertness in the field.

Keywords:

psychomotor test
mobile app
daytime sleepiness
Karolinska Sleepiness Scale
Epworth Sleepiness Scale

Authors:

Manaenkov A.E.

Institute of Higher Nervous Activity and Neurophysiology;
Lomonosov Moscow State University

Prokhorenko N.O.

Institute of Higher Nervous Activity and Neurophysiology;
Pirogov Russian National Research Medical University

Tkachenko O.N.

Institute of Higher Nervous Activity and Neurophysiology

Sveshnikov D.S.

Medical Institute of Peoples’ Friendship University of Russia

Dorokhov V.B.

Institute of Higher Nervous Activity and Neurophysiology

Received:

08.03.2023

Accepted:

16.03.2023

List of references:

  1. Dorokhov VB. Somnology and occupational safety. Zhurnal vysshei nervnoi Deiatelnosti im. I.P. Pavlova, 2013;63(1):33-47. (In Russ.). https://doi.org/10.7868/S0044467713010048
  2. Ulfberg J, Carter N, Talbäck M, Edling C. Excessive daytime sleepiness at work and subjective work performance in the general population and among heavy snorers and patients with obstructive sleep apnea. Chest. 1996;110(3):659-663.  https://doi.org/10.1378/chest.110.3.659
  3. Boyle LN, Tippin J, Paul A, Rizzo M. Driver Performance in the Moments Surrounding a Microsleep. Transp Res Part F Traffic Psychol Behav. 2008;11(2):126-136.  https://doi.org/10.1016/j.trf.2007.08.001
  4. Zhang F, Li W, Li H, et al. The effect of jet lag on the human brain: A neuroimaging study. Hum Brain Mapp. 2020;41(9):2281-2291. https://doi.org/10.1002/hbm.24945
  5. Ohayon MM. Epidemiology of Excessive Daytime Sleepiness. Sleep Medicine Clinics. 2006;1(1):9-16.  https://doi.org/10.1016/j.jsmc.2005.11.004
  6. Dinges DF. Sleep debt and scientific evidence. Sleep. 2004;27(6):1050-1052.
  7. Curcio G, Casagrande M, Bertini M. Sleepiness: evaluating and quantifying methods. International Journal of Psychophysiology. 2001;41(3):251-263.  https://doi.org/10.1016/S0167-8760(01)00138-6
  8. Akerstedt T, Gillberg M. Subjective and objective sleepiness in the active individual. Int J Neurosci. 1990;52(1-2):29-37.  https://doi.org/10.3109/00207459008994241
  9. Kaida K, Takahashi M, Åkerstedt T, et al. Validation of the Karolinska sleepiness scale against performance and EEG variables. Clinical Neurophysiology. 2006;117(7):1574-1581. https://doi.org/10.1016/j.clinph.2006.03.011
  10. Putilov AA, Donskaya OG. Construction and validation of the EEG analogues of the Karolinska sleepiness scale based on the Karolinska drowsiness test. Clin Neurophysiol. 2013;124(7):1346-1352. https://doi.org/10.1016/j.clinph.2013.01.018
  11. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14(6):540-545.  https://doi.org/10.1093/sleep/14.6.540
  12. Lapin BR, Bena JF, Walia HK, Moul DE. The Epworth Sleepiness Scale: Validation of One-Dimensional Factor Structure in a Large Clinical Sample. J Clin Sleep Med. 2018;14(8):1293-1301. https://doi.org/10.5664/jcsm.7258
  13. Rosenberg R, Babson K, Menno D, et al. Test—retest reliability of the Epworth Sleepiness Scale in clinical trial settings. Journal of Sleep Research. 2022;31(2):45-49.  https://doi.org/10.1111/jsr.13476
  14. Omobomi O, Quan SF. A Requiem for the Clinical Use of the Epworth Sleepiness Scale. J Clin Sleep Med. 2018;14(5):711-712.  https://doi.org/10.5664/jcsm.7086
  15. Arnardóttir H, Þorsteinsson H, Karlsson K. Dynamics of Sleep—Wake Cyclicity at Night Across the Human Lifespan. Frontiers in Neurology. 2010;1(8):345-351. 
  16. Yoshino K, Inomoto S, Iyama A, Sakoda S. Dynamic sleep stage transition process analysis in patients with Parkinson’s disease having sleep apnea syndrome. Informatics in Medicine Unlocked. 2021;25:100656. https://doi.org/10.1016/j.imu.2021.100656
  17. Ogilvie RD. The process of falling asleep. Sleep Med Rev. 2001;5(3):247-270.  https://doi.org/10.1053/smrv.2001.0145
  18. Prerau MJ, Hartnack KE, Obregon-Henao G, et al. Tracking the Sleep Onset Process: An Empirical Model of Behavioral and Physiological Dynamics. PLoS Comput Biol. 2014;10(10):e1003866. https://doi.org/10.1371/journal.pcbi.1003866
  19. Basner M, Moore TM, Nasrini J, Gur RC, Dinges DF. Response speed measurements on the psychomotor vigilance test: how precise is precise enough? Sleep. 2021;44(1):zsaa121. https://doi.org/10.1093/sleep/zsaa121
  20. Casagrande M, De Gennaro L, Violani C, et al. A finger-tapping task and a reaction time task as behavioral measures of the transition from wakefulness to sleep: which task interferes less with the sleep onset process. Sleep. 1997;20(4):301-312.  https://doi.org/10.1093/sleep/20.4.301
  21. Dorokhov VB. Alpha-spindle and K-complex — phase activation patterns during spontaneous recovery of psychomotor activity disorders at different stages of nap. Zhurn Vyssh Nervn Deyat. 2003;53(4):502-511. (In Russ.).
  22. Dorokhov VB, Tkachenko ON, Ushakov VL, Chernorizov AM. Neuronal Correlates of Spontaneous Awakening and Recovery of Psychomotor Performance. In: Velichkovsky BM, Balaban PM, Ushakov VL, eds. Advances in Cognitive Research, Artificial Intelligence and Neuroinformatics. Advances in Intelligent Systems and Computing. Springer International Publishing; 2021;429-435.  https://doi.org/10.1007/978-3-030-71637-0_49
  23. Agnew Jr. HW, Webb WB, Williams RL. The First Night Effect: An Eeg Study of Sleep. Psychophysiology. 1966;2(3):263-266.  https://doi.org/10.1111/j.1469-8986.1966.tb02650.x
  24. Curcio G, Ferrara M, Piergianni A, et al. Paradoxes of the first-night effect: a quantitative analysis of antero-posterior EEG topography. Clinical Neurophysiology. 2004;115(5):1178-1188. https://doi.org/10.1016/j.clinph.2003.12.018
  25. Tamaki M, Bang JW, Watanabe T, Sasaki Y. Night Watch in One Brain Hemisphere during Sleep Associated with the First-Night Effect in Humans. Curr Biol. 2016;26(9):1190-1194. https://doi.org/10.1016/j.cub.2016.02.063
  26. Button KS, Ioannidis JPA, Mokrysz C, et al. Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience. 2013;14(5):365-376.  https://doi.org/10.1038/nrn3475
  27. Yu Z, Guindani M, Grieco SF, et al. Beyond t test and ANOVA: applications of mixed-effects models for more rigorous statistical analysis in neuroscience research. Neuron. 2022;110(1):21-35.  https://doi.org/10.1016/j.neuron.2021.10.030
  28. Wickham H, Averick M, Bryan J, et al. Welcome to the Tidyverse. JOSS. 2019;4(43):1686. https://doi.org/10.21105/joss.01686
  29. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software. 2015;67:1-48.  https://doi.org/10.18637/jss.v067.i01

Close metadata

Contact the author
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.

Email Confirmation

An email was sent to test@gmail.com with a confirmation link. Follow the link from the letter to complete the registration on the site.

Email Confirmation

Contact us
If you have any questions, complaints or suggestions, please use this feedback form.
Email
Message
The publishing house "Media Sphere" does not provide treatment services, does not give recommendations on contacting medical institutions and specific specialists, on the prescription of medicines and dietary supplements.
Submit Application

You can become an author of one of our magazines, send a request and we will consider it in during the day.

Name
Phone
E-mail
Message
Login
Registration
E-mail
Password
Forgot Password?

Log in to the site using your account in one of the services

Password recovery
E-mail
Login
Register

We use cооkies to improve the performance of the site. By staying on our site, you agree to the terms of use of cооkies. To view our Privacy and Cookie Policy, please. click here.