An integrated multi-variable optimization approach to tailor ankle-foot orthosis stiffness to end-user needs

Area of Science:

• Biomechanics
• Rehabilitation Engineering
• Pediatric Gait Analysis

Background:

• Ankle-foot orthoses (AFOs) are crucial for gait assistance and rehabilitation.
• Current AFO stiffness recommendations are generalized and lack individual tailoring.
• Optimal AFO effectiveness hinges on precise stiffness customization.

Purpose of the Study:

• To introduce an integrated multi-variable optimization approach for personalized AFO stiffness.
• To simultaneously consider multiple gait aspects without predefined hierarchies.
• To allow user-specific priorities in optimizing AFO stiffness.

Main Methods:

• Ten children with cerebral palsy (CP) used a variable-stiffness AFO (inGAIT-VSO).
• Participants underwent trials with five distinct AFO stiffness configurations.
• An optimization method evaluated gait across kinematics, spatio-temporal, balance, user perception, and muscular control domains.

Main Results:

• The optimization method identified optimal AFO stiffness for each child, aligning gait with healthy patterns.
• Optimal stiffness varied significantly across participants and gait domains.
• Inclusion of physiotherapist and user priorities did not change optimal stiffness selection.

Conclusions:

• Optimizing AFO stiffness necessitates a multi-variable, personalized approach.
• The proposed method offers new avenues for AFO stiffness fine-tuning.
• Future research may integrate deep learning for efficient clinical application.