A review of current state-of-the-art control methods for lower-limb powered prostheses

R Gehlhar, M Tucker, AJ Young, AD Ames - Annual reviews in control, 2023 - Elsevier
Lower-limb prostheses aim to restore ambulatory function for individuals with lower-limb
amputations. While the design of lower-limb prostheses is important, this paper focuses on …

Active upper limb prostheses: A review on current state and upcoming breakthroughs

A Marinelli, N Boccardo, F Tessari… - Progress in …, 2023 - iopscience.iop.org
The journey of a prosthetic user is characterized by the opportunities and the limitations of a
device that should enable activities of daily living (ADL). In particular, experiencing a bionic …

Data-driven variable impedance control of a powered knee–ankle prosthesis for adaptive speed and incline walking

TK Best, CG Welker, EJ Rouse… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Most impedance-based walking controllers for powered knee–ankle prostheses use a finite
state machine with dozens of user-specific parameters that require manual tuning by …

Data-driven phase-based control of a powered knee-ankle prosthesis for variable-incline stair ascent and descent

RJ Cortino, TK Best, RD Gregg - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Powered knee-ankle prostheses can offer benefits over conventional passive devices during
stair locomotion by providing biomimetic net-positive work and active control of joint angles …

Continuous-time reinforcement learning control: A review of theoretical results, insights on performance, and needs for new designs

BA Wallace, J Si - IEEE Transactions on Neural Networks and …, 2023 - ieeexplore.ieee.org
This exposition discusses continuous-time reinforcement learning (CT-RL) for the control of
affine nonlinear systems. We review four seminal methods that are the centerpieces of the …

A new robotic knee impedance control parameter optimization method facilitated by inverse reinforcement learning

W Liu, R Wu, J Si, H Huang - IEEE Robotics and Automation …, 2022 - ieeexplore.ieee.org
Recent efforts in the design of intelligent controllers for configuring robotic prostheses have
demonstrated new possibilities in improving mobility and restoring locomotion for individuals …

Human-robotic prosthesis as collaborating agents for symmetrical walking

R Wu, J Zhong, B Wallace, X Gao… - Advances in Neural …, 2022 - proceedings.neurips.cc
This is the first attempt at considering human influence in the reinforcement learning control
of a robotic lower limb prosthesis toward symmetrical walking in real world situations. We …

Generating synthetic gait patterns based on benchmark datasets for controlling prosthetic legs

M Kim, LJ Hargrove - Journal of neuroengineering and rehabilitation, 2023 - Springer
Background Prosthetic legs help individuals with an amputation regain locomotion.
Recently, deep neural network (DNN)-based control methods, which take advantage of the …

Improving bionic limb control through reinforcement learning in an interactive game environment

K Freitag, R Laezza, J Zbinden, M Ortiz-Catalan - 2023 - openreview.net
Enhancing the accuracy and robustness of bionic limb controllers that decode motor intent is
a pressing challenge in the field of prosthetics. State-of-the-art research has mostly focused …

Continuous-Time Reinforcement Learning: New Design Algorithms With Theoretical Insights and Performance Guarantees

BA Wallace, J Si - IEEE Transactions on Neural Networks and …, 2024 - ieeexplore.ieee.org
Continuous-time reinforcement learning (CT-RL) methods hold great promise in real-world
applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially …