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Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
Published on: April 11, 2018
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Training multi-parameter gaits to reduce the knee adduction moment with data-driven models and haptic feedback.
Pete B Shull1, Kristen L Lurie, Mark R Cutkosky
1Department of Mechanical Engineering, Stanford University, Center for Design Research, Stanford, CA 94305-2232, USA. pshull@stanford.edu
Journal of Biomechanics
|April 5, 2011
Summary
This study shows that personalized gait retraining using haptic feedback can effectively reduce the knee adduction moment. Healthy individuals adopted new gaits in one session, significantly lowering knee joint stress.
Area of Science:
- Biomechanics
- Orthopedics
- Rehabilitation Engineering
Background:
- The knee adduction moment is a key factor in knee osteoarthritis progression.
- Current treatments often focus on managing symptoms rather than altering biomechanics.
- Novel approaches to reduce knee adduction moment are needed for early intervention.
Purpose of the Study:
- To evaluate subject-specific gait retraining for reducing the knee adduction moment.
- To determine if altered gaits reducing knee adduction moment by ≥30% can be adopted in one session.
- To assess the efficacy of haptic feedback on multiple kinematic gait parameters.
Main Methods:
- Nine healthy subjects underwent gait retraining using data-driven, subject-specific models.
- Wearable haptic devices provided real-time feedback on tibia angle, foot progression, and trunk sway.
- Subjects were trained to adopt novel gaits with simultaneous kinematic changes.
Main Results:
- All subjects successfully adopted altered gaits, reducing their knee adduction moments by 29-48%.
- Individual kinematic changes, particularly increased tibia angle, significantly reduced the knee adduction moment.
- Simultaneous adjustments to multiple parameters were achievable within a single training session.
Conclusions:
- Individualized, data-driven gait retraining is a viable strategy for reducing knee adduction moment.
- This approach shows potential as a non-invasive treatment for early-stage knee osteoarthritis.
- Future research should consider patient-specific factors like sensation and motor learning capabilities.
