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Preliminary Experiments with a Unified Controller for a Powered Knee-Ankle Prosthetic Leg Across Walking Speeds

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Journal Rep U S
Date 2017 Apr 11
PMID 28392969
Citations 27
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Abstract

This paper presents the experimental validation of a novel control strategy that unifies the entire gait cycle of a powered knee-ankle prosthetic leg without the need to switch between controllers for different periods of gait. Current control methods divide the gait cycle into several sequential periods each with independent controllers, resulting in many patient-specific control parameters and switching rules that must be tuned for a specific walking speed. The single controller presented is speed-invariant with a minimal number of control parameters to be tuned. A single, periodic virtual constraint is derived that exactly characterizes the desired actuated joint motion as a function of a mechanical phase variable across walking cycles. A single sensor was used to compute a phase variable related to the residual thigh angle's phase plane, which was recently shown to robustly represent the phase of non-steady human gait. This phase variable allows the prosthesis to synchronize naturally with the human user for intuitive, biomimetic behavior. A custom powered knee-ankle prosthesis was designed and built to implement the control strategy and validate its performance. A human subject experiment was conducted across multiple walking speeds (1 to 3 miles/hour) in a continuous sequence with the single phase-based controller, demonstrating its adaptability to the user's intended speed.

Citing Articles

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PMID: 39115988 PMC: 11559236. DOI: 10.1109/TNSRE.2024.3440257.


Powered knee and ankle prosthesis use with a K2 level ambulator: a case report.

Simon A, Finucane S, Ikeda A, Cotton R, Hargrove L Front Rehabil Sci. 2023; 4:1203545.

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Can a powered knee-ankle prosthesis improve weight-bearing symmetry during stand-to-sit transitions in individuals with above-knee amputations?.

Hunt G, Hood S, Gabert L, Lenzi T J Neuroeng Rehabil. 2023; 20(1):58.

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Seamless and intuitive control of a powered prosthetic leg using deep neural network for transfemoral amputees.

Kim M, Simon A, Hargrove L Wearable Technol. 2023; 3.

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