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Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.

التفاصيل البيبلوغرافية
العنوان: Are Gait Patterns during In-Lab Running Representative of Gait Patterns during Real-World Training? An Experimental Study.
المؤلفون: Davis JJ 4th; Department of Kinesiology, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA., Meardon SA; Department of Physical Therapy, East Carolina University, Greenville, NC 27858, USA., Brown AW; Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA., Raglin JS; Department of Kinesiology, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA., Harezlak J; Department of Epidemiology and Biostatistics, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA., Gruber AH; Department of Kinesiology, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA.
المصدر: Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 May 01; Vol. 24 (9). Date of Electronic Publication: 2024 May 01.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI, c2000-
مواضيع طبية MeSH: Running*/physiology , Gait*/physiology, Humans ; Male ; Biomechanical Phenomena/physiology ; Female ; Adult ; Wearable Electronic Devices ; Young Adult ; Gait Analysis/methods
مستخلص: Biomechanical assessments of running typically take place inside motion capture laboratories. However, it is unclear whether data from these in-lab gait assessments are representative of gait during real-world running. This study sought to test how well real-world gait patterns are represented by in-lab gait data in two cohorts of runners equipped with consumer-grade wearable sensors measuring speed, step length, vertical oscillation, stance time, and leg stiffness. Cohort 1 ( N = 49) completed an in-lab treadmill run plus five real-world runs of self-selected distances on self-selected courses. Cohort 2 ( N = 19) completed a 2.4 km outdoor run on a known course plus five real-world runs of self-selected distances on self-selected courses. The degree to which in-lab gait reflected real-world gait was quantified using univariate overlap and multivariate depth overlap statistics, both for all real-world running and for real-world running on flat, straight segments only. When comparing in-lab and real-world data from the same subject, univariate overlap ranged from 65.7% (leg stiffness) to 95.2% (speed). When considering all gait metrics together, only 32.5% of real-world data were well-represented by in-lab data from the same subject. Pooling in-lab gait data across multiple subjects led to greater distributional overlap between in-lab and real-world data (depth overlap 89.3-90.3%) due to the broader variability in gait seen across (as opposed to within) subjects. Stratifying real-world running to only include flat, straight segments did not meaningfully increase the overlap between in-lab and real-world running (changes of <1%). Individual gait patterns during real-world running, as characterized by consumer-grade wearable sensors, are not well-represented by the same runner's in-lab data. Researchers and clinicians should consider "borrowing" information from a pool of many runners to predict individual gait behavior when using biomechanical data to make clinical or sports performance decisions.
References: Sports Med. 2020 Apr;50(4):785-813. (PMID: 31802395)
Int J Sports Med. 2019 Aug;40(8):498-502. (PMID: 31288288)
Hum Mov Sci. 2020 Dec;74:102690. (PMID: 33132194)
Sports Biomech. 2014 Sep;13(3):259-66. (PMID: 25325770)
Sports Med. 2022 Aug;52(8):1863-1877. (PMID: 35247202)
Br J Sports Med. 2016 Jul;50(14):887-92. (PMID: 26644428)
J Biomech. 2019 Oct 11;95:109278. (PMID: 31472970)
Sports (Basel). 2020 Jul 20;8(7):. (PMID: 32698464)
J Orthop Sports Phys Ther. 2016 Jun;46(6):471-6. (PMID: 27117729)
J Strength Cond Res. 2013 Jun;27(6):1471-8. (PMID: 22990565)
Appl Bionics Biomech. 2020 Jun 23;2020:2041549. (PMID: 32676126)
Med Sci Sports Exerc. 2015 Nov;47(11):2473-9. (PMID: 26473759)
Sensors (Basel). 2021 Nov 08;21(21):. (PMID: 34770725)
J Sports Sci Med. 2005 Jun 01;4(2):144-52. (PMID: 24431970)
Gait Posture. 2022 Oct;98:195-202. (PMID: 36166957)
PLoS Comput Biol. 2023 Oct 19;19(10):e1011462. (PMID: 37856442)
Sports Med. 2019 Jul;49(7):1095-1115. (PMID: 31028658)
Orthop J Sports Med. 2021 May 25;9(5):23259671211011213. (PMID: 34104663)
Med Sci Sports Exerc. 2011 Feb;43(2):312-8. (PMID: 20543754)
Sensors (Basel). 2022 Feb 23;22(5):. (PMID: 35270869)
Front Bioeng Biotechnol. 2020 Feb 14;8:86. (PMID: 32117951)
J Biomech. 2019 Mar 6;85:187-192. (PMID: 30670328)
Front Sports Act Living. 2023 Apr 17;5:1085513. (PMID: 37139307)
Sports Health. 2022 Sep-Oct;14(5):710-716. (PMID: 34758661)
Sports Med. 2016 Jun;46(6):793-807. (PMID: 26816209)
J Sci Med Sport. 2012 Nov;15(6):554-60. (PMID: 22652147)
Med Sci Sports Exerc. 2020 Jun;52(6):1361-1366. (PMID: 31913243)
BMJ Open. 2019 Sep 6;9(9):e032627. (PMID: 31494626)
Gait Posture. 2019 Oct;74:176-181. (PMID: 31539798)
J Exp Psychol Hum Percept Perform. 1995 Feb;21(1):183-202. (PMID: 7707029)
Clin Biomech (Bristol, Avon). 2020 May;75:104991. (PMID: 32203864)
J Biomech. 1989;22(11-12):1217-27. (PMID: 2625422)
Int J Sports Phys Ther. 2014 Dec;9(7):948-58. (PMID: 25540710)
J Biomech. 2023 Jun;155:111617. (PMID: 37220709)
معلومات مُعتمدة: n/a American Society of Biomechanics; n/a American College of Sports Medicine Foundation, World Athletics Research Grant
فهرسة مساهمة: Keywords: biomechanics; depth statistics; free-living gait; unsupervised learning; wearable technology
تواريخ الأحداث: Date Created: 20240511 Date Completed: 20240511 Latest Revision: 20240513
رمز التحديث: 20240513
مُعرف محوري في PubMed: PMC11086149
DOI: 10.3390/s24092892
PMID: 38732998
قاعدة البيانات: MEDLINE
الوصف
تدمد:1424-8220
DOI:10.3390/s24092892