Feasibility of automatic knee kinematic feature learning for discriminating between individuals with and without a history of an anterior cruciate ligament reconstruction
The present study found that axial knee kinematics could serve as important biomarkers of an ACLr, potentially representing a modifiable feature for osteoarthritis treatment and prevention. These findings demonstrate the feasibility of early knee osteoarthritis detection using biomechanical biomarkers, providing preliminary evidence for the use of wearable sensors outside clinical settings and underscoring the possibilities for at-home monitoring.
Authors
- Benjamin Butler (ORCID: https://orcid.org/0000-0001-7831-0111)
- David W. Evans (ORCID: https://orcid.org/0000-0002-3990-5494)
- Zainab Altai (ORCID: https://orcid.org/0000-0002-1654-3857)
- Behnam Gholami (ORCID: https://orcid.org/0000-0003-0338-1921)
- Qichang Mei (ORCID: https://orcid.org/0000-0003-1113-877X)
- Bernard X. W. Liew (ORCID: https://orcid.org/0000-0002-7057-7548)
- David Hollinger (ORCID: https://orcid.org/0000-0003-0689-9531)
- Benedict Z W Low
Institutions
- University of Essex (GB)
- University of Auckland (NZ)
- Auckland University of Technology (NZ)
- University of Birmingham (GB)
Publication Details
- Journal
- Clinical Biomechanics
- Published
- 2025-09-25
- DOI
- https://doi.org/10.1016/j.clinbiomech.2025.106673
- Primary Topic
- Knee injuries and reconstruction techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00