Dynamic Ankle Foot Orthosis Controller for Crouch Gait Optimization
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Solution Overview
Problem
Selecting an optimal Ankle Foot Orthosis (AFO) for individuals with cerebral palsy (CP) is challenging due to the difficulty in predicting how a specific design will impact muscle action and reduce the energy cost of walking, as conventional AFOs do not effectively address the trade-off between push-off power and flexion angle.
Innovation Solution
A method and system for personalized and optimal selection of AFOs using motion-captured crouch gait data, joint ankle angle kinematics, and musculoskeletal human lower limb models (MHLLM) to compute AFO torque, muscle forces, and response metrics, ranking AFO controllers based on muscle impulse, yank, co-activation, and energetic cost of walking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a solid AFO is used to counteract excessive knee flexion, then knee kinematics are normalized effectively, but push-off power is not reduced
Solution Approach 1:
The patent transitions from static solid AFO to dynamic AFO with variable stiffness characteristics. The dynamic AFO adapts its mechanical properties during the gait cycle, providing rigid support during swing phase for knee stability and flexible compliance during stance phase for push-off power generation.
Solution Approach 2:
The patent employs AFOs with adjustable stiffness parameters and equilibrium angles. By modifying these parameters, the AFO can optimize the trade-off between knee flexion control and push-off power generation, allowing customization for individual patient needs and gait phases.
2Power
If a spring-like AFO is used to enhance push-off power, then push-off power is improved, but knee flexion reduction is limited
Solution Approach 1:
The dynamic AFO system provides time-varying stiffness characteristics that switch between flexible (for push-off) and rigid (for knee control) states during different phases of the gait cycle, resolving the contradiction between power enhancement and stability maintenance.
Solution Approach 2:
The AFO is functionally segmented into different operational phases: swing phase control for knee flexion normalization and stance phase compliance for push-off power enhancement. This segmentation allows each function to be optimized independently.
3Reliability
If passive AFOs are prescribed to assist ankle dynamics, then gait kinematics are improved and bone deformity is prevented, but the selection of optimal AFO design is challenging
Solution Approach 1:
The patent utilizes adjustable parameters including stiffness, equilibrium angle, and damping coefficients to optimize AFO performance. These parameters can be tuned to match individual patient characteristics and gait patterns, simplifying the selection process while maintaining high reliability.
Solution Approach 2:
The system incorporates gait analysis feedback to evaluate AFO performance and guide selection. By measuring actual gait parameters and comparing them against target values, the optimal AFO design can be identified based on quantitative performance metrics rather than trial-and-error.
Data Source
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AI summary
In state of art techniques, it is challenging to predict how a specific Ankle Foot Orthosis (AFO) will impact muscle action and reduce an energy cost of walking for individual subjects. The disclosed method focusses on personalized and optimal selection of an AFO controller using an AFO torque, and a plurality joint ankle angles of each of a plurality of AFO controllers integrated with a musculoskeletal human lower limb model (MHLLM). The plurality of muscle forces is computed using the MHLLM for each of the plurality of AFO controllers. Further the method computes a plurality of muscle response metrics, from the plurality of muscle forces and an additional joint torque for each of the AFO controllers. Further the method combines the plurality of muscle response metrics which enables the selection of a personalized optimal AFO controller among the plurality of AFO controllers of a (cerebral palsy) CP subject.