Generation of subject-specific, dynamic, multi-segment ankle and foot models to improve the design of foot and ankle foot orthoses

Recruiting

Conditions: 10012653
10043237
CVA
general foot problems

Registration Number: NL-OMON38031

Lead Sponsor: orthopaedie

Brief Summary: Not available

Detailed Description: Not available

Recruitment & Eligibility

Status: Recruiting

Sex: Not specified

Target Recruitment: 12

Inclusion Criteria

Group healthy feet:
• Physically able to perform testing (able to walk at least 20 meters barefoot and unaided)
• 38 < Shoe size < 44 (EUR), 5.5 < Shoe size < 9.5 (UK)
• 18 < age < 50 year
• Fully competent and able to give informed consent
Group pathological feet:
• Three groups, one group who would be prescribed pressure relieveing orthotics (e.g. diabetic patients), one group who would be prescribed orthotics to improve alignment (e.g. flexible flat foot deformities), and a final group of stroke patients who would be prescribed an ankle foot orthosis for motion control. The included CVA patients will be fully competent and able to give informed consent.
• Physically able to perform testing (able to walk at least 20 meters barefoot and unaided)
• 38 < Shoe size < 44 (EUR), 5.5 < Shoe size < 9.5 (UK)
• 18 < age < 50
• In need of an (ankle-)foot orthosis
• Fully competent and able to give informed consent

Exclusion Criteria

Group healthy feet
• Footproblems, requiring medical treatment
• Lower extremity problems
• Diabetes Mellitus
• Rheumatoid Arthritis
• Pregnant and lactating women
Group pathological feet
• Lower extremity problems, causing gait variation
• Pregnant and lactating women

Study & Design

Study Type: Observational invasive

Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
<p>This study is a feasibility/pilot study. The primary aim of the study is to<br /><br>collect the imaging and motion analysis data that is required to develop and<br /><br>validate accurate computational models of the foot and ankle, and incorporate<br /><br>these into high fidelity dynamic simulations. As such, the outcome measure<br /><br>could be defined as how close to real life these simulations are shown to be.<br /><br>This will be achieved by validating the model against plantar pressure data and<br /><br>surface EMG data taken during the gait analysis. </p><br>

Secondary Outcome Measures