Experimental Demonstration of the Lower Leg Trajectory Error Framework Using Physiological Data as Inputs.

Area of Science:

• Biomechanics
• Prosthetics Engineering
• Rehabilitation Science

Background:

• Characterizing passive prosthetic feet is crucial for understanding amputee gait.
• The link between prosthetic mechanical design and biomechanical performance lacks a fundamental physics explanation.
• Existing methods struggle to quantitatively optimize prosthetic components for desired gait outcomes.

Purpose of the Study:

• To introduce and evaluate a novel framework, the lower leg trajectory error (LLTE) framework, for optimizing prosthetic foot design.
• To quantitatively link prosthetic mechanical properties (stiffness, geometry) to biomechanical performance using a physics-based approach.
• To demonstrate the framework's ability to predict and achieve desired biomechanical responses in prosthetic feet.

Main Methods:

• Developed the lower leg trajectory error (LLTE) framework to quantitatively optimize prosthetic foot constitutive models.
• Matched prosthetic feet to reference kinematic and kinetic datasets.
• Tested a passive prototype prosthetic foot with adjustable ankle stiffness on a unilateral transtibial amputee.

Main Results:

• The LLTE-optimal ankle stiffness condition allowed the amputee to replicate physiological target data within 16% root-mean-square (RMS) error.
• Measured kinematic variables closely matched target kinematics, achieving within 4% RMS error.
• Lower LLTE values consistently resulted in less deviation from target kinematic data across various stiffness settings.

Conclusions:

• The LLTE framework effectively optimizes prosthetic foot design for improved amputee gait.
• Prosthetic feet designed using the LLTE framework show potential for enhanced user benefits and customization.
• The framework's design-agnostic nature allows broad application in developing and tailoring prosthetic devices.