Determining Individualised Gait Modification Strategies to Reduce Knee Joint Moments in Alkaptonuria Patients Using Real-time Feedback
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Alkaptonuria
- Sponsor
- Liverpool John Moores University
- Enrollment
- 30
- Primary Endpoint
- Change from baseline 3D knee joint moment impulse after intervention
- Last Updated
- 5 years ago
Overview
Brief Summary
This study evaluates the efficacy of a gait modification intervention using real-time biofeedback on reducing the knee joint loading in Alkaptonuria patients during treadmill walking. It will also assess whether the individualised adopted gait modification can be retained without feedback and during over ground walking.
Detailed Description
Alkaptonuria (AKU) is a degenerative disease affecting the cartilage of the joints. The disease affects movement function, particularly walking/gait which is an important activity of daily living. It is believed that increased joint loading measured by the moments acting upon the joints, contributes to the degeneration of joint cartilage in Alkaptonuria, particularly in the weight bearing joints such as the knee and hips, resulting in accelerated progression of painful symptoms. Currently there is no cure for Alkaptonuria and the current management includes joint replacement surgery. Gait modification strategy interventions could be a non-invasive alternative which could delay the time to surgical interventions by reducing or altering joint loading and stalling the progression of disease. The aims of this study are 1) to determine if individualised gait modification strategies can be used to reduce the 3D knee joint loading, 2) to determine if the gait modifications can be retained without feedback during over ground walking and 3) to determine the individualised gait modification strategies adopted by AKU patients. Gait data will be measured and quantified using the non-invasive typical clinical gait analysis set up, using 3D motion capture combined with force data whereby joint angles, moments and powers can be calculated in all 3 planes of motion during treadmill walking. The intervention will involve real-time biofeedback using Motek's M-Gait treadmill. Due to the heterogeneity of the sample, each AKU patient will act as their own control. Gait data will be compared pre- and post-intervention and a validated pain score will be used to identify any patterns with knee pain and adopted gait modifications.
Investigators
Hannah Shepherd
Associate Lecturer in Clinical Biomechanics
Liverpool John Moores University
Eligibility Criteria
Inclusion Criteria
- •The diagnosis of Alkaptonuria
- •Able to understand written and spoken English.
- •Willing and able to give informed consent to participate
- •Above the age of 18.
Exclusion Criteria
- •The reliance on or use of a walking aid.
- •Any previous lower limb joint replacements.
- •Any severe pain or unable to walk comfortably and consecutively for 20 minutes.
Outcomes
Primary Outcomes
Change from baseline 3D knee joint moment impulse after intervention
Time Frame: At baseline and immediately after the intervention
This represents the knee joint load during walking measured from kinematic and kinetic data obtained during the 3D gait analysis
Secondary Outcomes
- Change from baseline joint moments after intervention(At baseline and immediately after the intervention)
- Knee injury and Osteoarthritis Outcome Score(Pre-intervention)
- Change from baseline joint angles after intervention(At baseline and immediately after the intervention)
- Change from baseline joint powers after intervention(At baseline and immediately after the intervention)