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Related Concept Videos

Knee Joint01:23

Knee Joint

The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris group...

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Related Experiment Video

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Movement Retraining using Real-time Feedback of Performance
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Shared Strides: Community-based, high-throughput biomechanics data collection in knee osteoarthritis.

Jenna M Qualter1, Ryan C McCloskey2, Kathryn A Stofer3

  • 1Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA.

Medrxiv : the Preprint Server for Health Sciences
|April 3, 2026
PubMed
Summary

Community-based biomechanics assessments for knee osteoarthritis (OA) were well-received, improving research engagement. This approach facilitated larger, more representative sample sizes by utilizing accessible community sites.

Keywords:
acceptabilityactivities of daily livingfirst-time research participantsmarkerless motion captureresearch accessibilitywalk-in recruitment

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Area of Science:

  • Biomechanics
  • Osteoarthritis Research
  • Community-Based Research

Background:

  • Knee osteoarthritis (OA) research often faces challenges in participant recruitment and engagement.
  • High-throughput biomechanics assessments can provide valuable insights into OA.
  • Traditional research settings may limit accessibility for OA populations.

Purpose of the Study:

  • To assess the acceptability of a high-throughput, community-based biomechanics protocol for individuals with knee OA.
  • To evaluate the recruitment implications of conducting biomechanics assessments at community sites.
  • To compare participant engagement and preferences between on-campus and community-based research locations.

Main Methods:

  • A cross-sectional study was conducted during the Shared Strides Study.
  • High-throughput markerless biomechanics data were collected during activities of daily living (ADLs) at community sites.
  • Participant acceptability was assessed via a custom questionnaire; recruitment characteristics were compared across sites.

Main Results:

  • The community-based biomechanics data collection approach was well-received by participants.
  • Community sites showed higher engagement from walk-in and new research participants (40%).
  • Familiarity with and proximity to data collection sites influenced research engagement.

Conclusions:

  • Integrating markerless motion capture with community-based research enhances participant experience.
  • This approach can facilitate larger, more heterogeneous sample sizes in OA biomechanics research.
  • Community-based methods may reduce bias and homogeneity in current OA research.