دورية أكاديمية
Relation of gait measures with mild unilateral knee pain during walking using machine learning.
العنوان: | Relation of gait measures with mild unilateral knee pain during walking using machine learning. |
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المؤلفون: | Bacon KL; Boston University Chobanian & Avedisian School of Medicine, 650 Albany Street, Suite X200, Boston, MA, 02118, USA. kbacon@bu.edu., Felson DT; Boston University Chobanian & Avedisian School of Medicine, 650 Albany Street, Suite X200, Boston, MA, 02118, USA., Jafarzadeh SR; Boston University Chobanian & Avedisian School of Medicine, 650 Albany Street, Suite X200, Boston, MA, 02118, USA., Kolachalama VB; Boston University Chobanian & Avedisian School of Medicine, 650 Albany Street, Suite X200, Boston, MA, 02118, USA., Hausdorff JM; Tel Aviv University, Tel Aviv, Israel., Gazit E; Tel Aviv Sourasky Medical Center, Tel Aviv, Israel., Segal NA; University of Kansas Medical Center, Kansas City, USA., Lewis CE; University of Alabama at Birmingham, Birmingham, AL, USA., Nevitt MC; University of California, San Francisco, San Francisco, CA, USA., Kumar D; Boston University Chobanian & Avedisian School of Medicine, 650 Albany Street, Suite X200, Boston, MA, 02118, USA. |
مؤلفون مشاركون: | Multicenter Osteoarthritis Study Investigators |
المصدر: | Scientific reports [Sci Rep] 2022 Dec 23; Vol. 12 (1), pp. 22200. Date of Electronic Publication: 2022 Dec 23. |
نوع المنشور: | Observational Study; Multicenter Study; Journal Article; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural |
اللغة: | English |
بيانات الدورية: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: London : Nature Publishing Group, copyright 2011- |
مواضيع طبية MeSH: | Gait* , Osteoarthritis, Knee*, Humans ; Female ; Middle Aged ; Male ; Cross-Sectional Studies ; Walking ; Knee Joint ; Pain ; Machine Learning ; Biomechanical Phenomena |
مستخلص: | Gait alterations in those with mild unilateral knee pain during walking may provide clues to modifiable alterations that affect progression of knee pain and osteoarthritis (OA). To examine this, we applied machine learning (ML) approaches to gait data from wearable sensors in a large observational knee OA cohort, the Multicenter Osteoarthritis (MOST) study. Participants completed a 20-m walk test wearing sensors on their trunk and ankles. Parameters describing spatiotemporal features of gait and symmetry, variability and complexity were extracted. We used an ensemble ML technique ("super learning") to identify gait variables in our cross-sectional data associated with the presence/absence of unilateral knee pain. We then used logistic regression to determine the association of selected gait variables with odds of mild knee pain. Of 2066 participants (mean age 63.6 [SD: 10.4] years, 56% female), 21.3% had mild unilateral pain while walking. Gait parameters selected in the ML process as influential included step regularity, sample entropy, gait speed, and amplitude dominant frequency, among others. In adjusted cross-sectional analyses, lower levels of step regularity (i.e., greater gait variability) and lower sample entropy(i.e., lower gait complexity) were associated with increased likelihood of unilateral mild pain while walking [aOR 0.80 (0.64-1.00) and aOR 0.79 (0.66-0.95), respectively]. (© 2022. The Author(s).) |
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معلومات مُعتمدة: | U01 AG018832 United States AG NIA NIH HHS; U01 AG018820 United States AG NIA NIH HHS; R01 HL159620 United States HL NHLBI NIH HHS; K01 AR069720 United States AR NIAMS NIH HHS; P30 AR072571 United States AR NIAMS NIH HHS; U01 AG019069 United States AG NIA NIH HHS; P60 AR047785 United States AR NIAMS NIH HHS; R43 DK134273 United States DK NIDDK NIH HHS; U01 AG018947 United States AG NIA NIH HHS |
فهرسة مساهمة: | Investigator: DT Felson; NA Segal; CE Lewis; MC Nevitt |
تواريخ الأحداث: | Date Created: 20221223 Date Completed: 20221227 Latest Revision: 20231031 |
رمز التحديث: | 20231031 |
مُعرف محوري في PubMed: | PMC9789148 |
DOI: | 10.1038/s41598-022-21142-2 |
PMID: | 36564397 |
قاعدة البيانات: | MEDLINE |
تدمد: | 2045-2322 |
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DOI: | 10.1038/s41598-022-21142-2 |