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DOI: 10.1055/s-0043-1776748
Association between Self-reported Sleep Quality and Single-task Gait in Young Adults: A Study Using Machine Learning
Sources of Funding The authors declare that they have received no funding from agencies in the public, private or non-profit sector for the conduction of the present study.![](https://www.thieme-connect.de/media/10.1055-s-00056804/202304/lookinside/thumbnails/10-1055-s-0043-1776748_1010-1.jpg)
Abstract
Objective The objective of the present study was to find biomechanical correlates of single-task gait and self-reported sleep quality in a healthy, young population by replicating a recently published study.
Materials and Methods Young adults (n = 123) were recruited and were asked to complete the Pittsburgh Sleep Quality Inventory to assess sleep quality. Gait variables (n = 53) were recorded using a wearable inertial measurement sensor system on an indoor track. The data were split into training and test sets and then different machine learning models were applied. A post-hoc analysis of covariance (ANCOVA) was used to find statistically significant differences in gait variables between good and poor sleepers.
Results AdaBoost models reported the highest correlation coefficient (0.77), with Support-Vector classifiers reporting the highest accuracy (62%). The most important features associated with poor sleep quality related to pelvic tilt and gait initiation. This indicates that overall poor sleepers have decreased pelvic tilt angle changes, specifically when initiating gait coming out of turns (first step pelvic tilt angle) and demonstrate difficulty maintaining gait speed.
Discussion The results of the present study indicate that when using traditional gait variables, single-task gait has poor accuracy prediction for subjective sleep quality in young adults. Although the associations in the study are not as strong as those previously reported, they do provide insight into how gait varies in individuals who report poor sleep hygiene. Future studies should use larger samples to determine whether single task-gait may help predict objective measures of sleep quality especially in a repeated measures or longitudinal or intervention framework.
Publikationsverlauf
Eingereicht: 13. Oktober 2022
Angenommen: 25. Januar 2023
Artikel online veröffentlicht:
22. November 2023
© 2023. Brazilian Sleep Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)
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References
- 1 Institute of Medicine (US) Committee on Sleep Medicine and Research. Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem [Internet]. Colten HR, Altevogt BM. editors. Washington (DC): National Academies Press (US); 2006. [cited 2020 Apr 18]. (The National Academies Collection: Reports funded by National Institutes of Health). Available from: http://www.ncbi.nlm.nih.gov/books/NBK19960/
- 2 Chaput JP, Dutil C, Sampasa-Kanyinga H. Sleeping hours: what is the ideal number and how does age impact this?. Nat Sci Sleep 2018; 10: 421-430
- 3 Youngstedt SD, Goff EE, Reynolds AM. et al. Has adult sleep duration declined over the last 50+ years?. Sleep Med Rev 2016; 28: 69-85
- 4 Siengsukon CF, Al-Dughmi M, Stevens S. Sleep Health Promotion: Practical Information for Physical Therapists. Phys Ther 2017; 97 (08) 826-836
- 5 Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol 2005; 25 (01) 117-129
- 6 Fukuchi CA, Fukuchi RK, Duarte M. Effects of walking speed on gait biomechanics in healthy participants: a systematic review and meta-analysis. Syst Rev 2019; 8 (01) 153
- 7 Bahureksa L, Najafi B, Saleh A. et al. The Impact of Mild Cognitive Impairment on Gait and Balance: A Systematic Review and Meta-Analysis of Studies Using Instrumented Assessment. Gerontology 2017; 63 (01) 67-83
- 8 Beauchet O, Berrut G. [Gait and dual-task: definition, interest, and perspectives in the elderly]. Psychol Neuropsychiatr Vieil 2006; 4 (03) 215-225
- 9 Bernstein JPK, De Vito A, Weitzner DS. et al. Examining Relationships between Multiple Self-Reported Sleep Measures and Gait Domains in Cognitively Healthy Older Adults. Gerontology 2020; 66 (01) 47-54
- 10 Goldman SE, Stone KL, Ancoli-Israel S. et al. Poor sleep is associated with poorer physical performance and greater functional limitations in older women. Sleep 2007; 30 (10) 1317-1324
- 11 Agmon M, Shochat T, Kizony R. Sleep quality is associated with walking under dual-task, but not single-task performance. Gait Posture 2016; 49: 127-131
- 12 Grobe S, Kakar RS, Smith ML, Mehta R, Baghurst T, Boolani A. Impact of cognitive fatigue on gait and sway among older adults: A literature review. Prev Med Rep 2017; 6: 88-93
- 13 Kearney FC, Harwood RH, Gladman JR, Lincoln N, Masud T. The relationship between executive function and falls and gait abnormalities in older adults: a systematic review. Dement Geriatr Cogn Disord 2013; 36 (1-2): 20-35
- 14 Liu X, Sun B, Zhang Z, Wang Y, Tang H, Zhu T. Gait can reveal sleep quality with machine learning models. PLoS One 2019; 14 (09) e0223012
- 15 Bramah C, Preece SJ, Gill N, Herrington L. Is there a pathological gait associated with common soft tissue running injuries?. Am J Sports Med 2018; 46 (12) 3023-3031
- 16 Springer S, Gottlieb U, Lozin M. Spatiotemporal gait parameters as predictors of lower-limb overuse injuries in military training. ScientificWorldJournal 2016; 2016: 5939164
- 17 Cimolin V, Galli M. Summary measures for clinical gait analysis: a literature review. Gait Posture 2014; 39 (04) 1005-1010
- 18 Wren TAL, Gorton III GE, Õunpuu S, Tucker CA. Efficacy of clinical gait analysis: A systematic review. Gait Posture 2011; 34 (02) 149-153
- 19 Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989; 28 (02) 193-213
- 20 Mollayeva T, Thurairajah P, Burton K, Mollayeva S, Shapiro CM, Colantonio A. The Pittsburgh sleep quality index as a screening tool for sleep dysfunction in clinical and non-clinical samples: A systematic review and meta-analysis. Sleep Med Rev 2016; 25: 52-73
- 21 Paul SS, Walther RG, Beseris EA, Dibble LE, Lester ME. Feasibility and Validity of Discriminating Yaw Plane Head-on-Trunk Motion Using Inertial Wearable Sensors. IEEE Trans Neural Syst Rehabil Eng 2017; 25 (12) 2347-2354
- 22 Dewey DC, Miocinovic S, Bernstein I. et al. Automated gait and balance parameters diagnose and correlate with severity in Parkinson disease. J Neurol Sci 2014; 345 (1-2): 131-138
- 23 Moumdjian L, Maes PJ, Dalla Bella S. et al. Detrended fluctuation analysis of gait dynamics when entraining to music and metronomes at different tempi in persons with multiple sclerosis. Sci Rep 2020; 10 (01) 12934
- 24 Mancini M, King L, Salarian A, Holmstrom L, McNames J, Horak FB. Mobility Lab to Assess Balance and Gait with Synchronized Body-worn Sensors. J Bioeng Biomed Sci 2011; (Suppl. 01) 007
- 25 Alasadi SA, Bhaya WS. Review of data preprocessing techniques in data mining. J Eng Appl Sci (Asian Res Publ Netw) 2017; 12 (16) 4102-4107
- 26 Zhao X, Yu B, Liu Y. et al. Estimation of poverty using random forest regression with multi-source data: A case study in Bangladesh. Remote Sens 2019; 11 (04) 375
- 27 Research LA. Education Institute I, Center RLANR, Service RLANRCP, Department RLANRCPT. Observational Gait Analysis [Internet]. Los Amigos Research and Education Institute, Rancho Los Amigos National Rehabilitation Center; 2001. . Available from: https://books.google.com/books?id=sZdMPgAACAAJ
- 28 Huisinga JM, Mancini M, St George RJ, Horak FB. Accelerometry reveals differences in gait variability between patients with multiple sclerosis and healthy controls. Ann Biomed Eng 2013; 41 (08) 1670-1679
- 29 Spain RI, St George RJ, Salarian A. et al. Body-worn motion sensors detect balance and gait deficits in people with multiple sclerosis who have normal walking speed. Gait Posture 2012; 35 (04) 573-578
- 30 Diamond LE, Wrigley TV, Bennell KL, Hinman RS, O'Donnell J, Hodges PW. Hip joint biomechanics during gait in people with and without symptomatic femoroacetabular impingement. Gait Posture 2016; 43: 198-203
- 31 Svoboda Z, Janura M, Kutilek P, Janurova E. Relationships between movements of the lower limb joints and the pelvis in open and closed kinematic chains during a gait cycle. J Hum Kinet 2016; 51: 37-43
- 32 Forsell C, Conradsson D, Paquette C, Franzén E. Reducing gait speed affects axial coordination of walking turns. Gait Posture 2017; 54: 71-75
- 33 Dietch JR, Taylor DJ, Sethi K, Kelly K, Bramoweth AD, Roane BM. Psychometric evaluation of the PSQI in US college students. J Clin Sleep Med 2016; 12 (08) 1121-1129
- 34 Guillodo E, Lemey C, Simonnet M. et al; HUGOPSY Network. Clinical Applications of Mobile Health Wearable-Based Sleep Monitoring: Systematic Review. JMIR Mhealth Uhealth 2020; 8 (04) e10733
- 35 Lemke MR, Wendorff T, Mieth B, Buhl K, Linnemann M. Spatiotemporal gait patterns during over ground locomotion in major depression compared with healthy controls. J Psychiatr Res 2000; 34 (4-5): 277-283
- 36 Feldman R, Schreiber S, Pick CG, Been E. Gait, balance, mobility and muscle strength in people with anxiety compared to healthy individuals. Hum Mov Sci 2019; 67: 102513
- 37 Umemura GS, Pinho JP, Duysens J, Krebs HI, Forner-Cordero A. Sleep deprivation affects gait control. Sci Rep 2021; 11 (01) 21104
- 38 Furtado F, Gonçalves BD, Abranches ILL, Abrantes AF, Forner-Cordero A. Chronic Low Quality Sleep Impairs Postural Control in Healthy Adults. PLoS One 2016; 11 (10) e0163310
- 39 Kobayashi Y, Hobara H, Heldoorn TA, Kouchi M, Mochimaru M. Age-independent and age-dependent sex differences in gait pattern determined by principal component analysis. Gait Posture 2016; 46: 11-17