Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Observational Study
. 2024 Jul;76(7):984-992.
doi: 10.1002/acr.25327. Epub 2024 Apr 17.

Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study

Kathryn L Bacon  1 , David T Felson  1 , S Reza Jafarzadeh  1 , Vijaya B Kolachalama  1 , Jeffrey M Hausdorff  2 , Eran Gazit  3 , Joshua J Stefanik  4 , Patrick Corrigan  5 , Neil A Segal  6 , Cora E Lewis  7 , Michael C Nevitt  8 , Deepak Kumar  1
Affiliations
Observational Study

Gait Alterations and Association With Worsening Knee Pain and Physical Function: A Machine Learning Approach With Wearable Sensors in the Multicenter Osteoarthritis Study

Kathryn L Bacon et al. Arthritis Care Res (Hoboken). 2024 Jul.

Abstract

Objective: The objective of this study was to identify gait alterations related to worsening knee pain and worsening physical function, using machine learning approaches applied to wearable sensor-derived data from a large observational cohort.

Methods: Participants in the Multicenter Osteoarthritis Study (MOST) completed a 20-m walk test wearing inertial sensors on their lower back and ankles. Parameters describing spatiotemporal features of gait were extracted from these data. We used an ensemble machine learning technique ("super learning") to optimally discriminate between those with and without worsening physical function and, separately, those with and without worsening pain over two years. We then used log-binomial regression to evaluate associations of the top 10 influential variables selected with super learning with each outcome. We also assessed whether the relation of altered gait with worsening function was mediated by changes in pain.

Results: Of 2,324 participants, 29% and 24% had worsening knee pain and function over two years, respectively. From the super learner, several gait parameters were found to be influential for worsening pain and for worsening function. After adjusting for confounders, greater gait asymmetry, longer average step length, and lower dominant frequency were associated with worsening pain, and lower cadence was associated with worsening function. Worsening pain partially mediated the association of cadence with function.

Conclusion: We identified gait alterations associated with worsening knee pain and those associated with worsening physical function. These alterations could be assessed with wearable sensors in clinical settings. Further research should determine whether they might be therapeutic targets to prevent worsening pain and worsening function.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Selection of Participants for analysis dataset from MOST cohort
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1204–22. - PMC - PubMed
    1. Kolasinski SL, Neogi T, Hochberg MC, Oatis C, Guyatt G, Block J, et al. 2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee. Arthritis Rheumatol. 2020;72(2):220–33. - PMC - PubMed
    1. D’Souza N, Charlton J, Grayson J, Kobayashi S, Hutchison L, Hunt M, et al. Are biomechanics during gait associated with the structural disease onset and progression of lower limb osteoarthritis? A systematic review and meta-analysis. Osteoarthritis Cartilage. 2022;30(3):381–94. - PubMed
    1. Miyazaki T, Wada M, Kawahara H, Sato M, Baba H, Shimada S. Dynamic load at baseline can predict radiographic disease progression in medial compartment knee osteoarthritis. Annals of the rheumatic diseases. 2002;61(7):617–22. - PMC - PubMed
    1. Wink AE, Gross KD, Brown CA, Guermazi A, Roemer F, Niu J, et al. Varus thrust during walking and the risk of incident and worsening medial tibiofemoral MRI lesions: the Multicenter Osteoarthritis Study. Osteoarthritis and cartilage. 2017;25(6):839–45. - PMC - PubMed

Publication types

LinkOut - more resources