Autonomous motion and control of lower limb exoskeleton rehabilitation robot DOI Creative Commons
Xueshan Gao, Pengfei Zhang, Xuefeng Peng

et al.

Frontiers in Bioengineering and Biotechnology, Journal Year: 2023, Volume and Issue: 11

Published: July 14, 2023

Introduction: The lower limb exoskeleton rehabilitation robot should perform gait planning based on the patient's motor intention and training status provide multimodal robust control schemes in strategy to enhance patient participation. Methods: This paper proposes an adaptive particle swarm optimization admittance algorithm (APSOAC), which adaptively optimizes weights learning factors of PSO avoid problem falling into local optimal points. proposed improved adjusts stiffness damping parameters online reduce interaction force between plans desired profile. In addition, this study a dual RBF neural network sliding mode controller (DRNNASMC) track profile, compensate for frictional forces external perturbations generated human-robot using network, calculate required moments each joint dynamics model, stability analysis Lyapunov theory. Results discussion: Finally, efficiency APSOAC DRNNASMC algorithms is demonstrated by active passive walking experiments with three healthy subjects, respectively.

Language: Английский

Upper limb rehabilitation using robotic exoskeleton systems: a systematic review DOI

Naqash Rehmat,

Jie Zuo, Wei Meng

et al.

International Journal of Intelligent Robotics and Applications, Journal Year: 2018, Volume and Issue: 2(3), P. 283 - 295

Published: Aug. 17, 2018

Language: Английский

Citations

116
Machine Learning in Robot-Assisted Upper Limb Rehabilitation: A Focused Review DOI
Qingsong Ai, Zemin Liu, Wei Meng

et al.

IEEE Transactions on Cognitive and Developmental Systems, Journal Year: 2021, Volume and Issue: 15(4), P. 2053 - 2063

Published: Aug. 10, 2021

Robot-assisted rehabilitation, which can provide repetitive, intensive, and high-precision physics training, has a positive influence on the motor function recovery of stroke patients. Current robots need to be more intelligent reliable in clinical practice. Machine learning algorithms (MLAs) are able learn from data predict future unknown conditions, is benefit improve effectiveness robot-assisted rehabilitation. In this article, we conduct focused review machine learning-based methods for upper limb First, current status rehabilitation presented. Then, outline analyze designs applications MLAs movement intention recognition, human–robot interaction control, quantitative assessment function. Meanwhile, discuss directions MLAs-based robotic This article provides summary contributes design development advanced medical devices.

Language: Английский

Citations

47
α-Variable adaptive model free control of iReHave upper-limb exoskeleton DOI
Haoping Wang, Hui Xu, Yang Tian

et al.

Advances in Engineering Software, Journal Year: 2020, Volume and Issue: 148, P. 102872 - 102872

Published: July 1, 2020

Language: Английский

Citations

49
Neural-network-enhanced torque estimation control of a soft wearable exoskeleton for elbow assistance DOI
Qingcong Wu, Bai Chen, Hongtao Wu

et al.

Mechatronics, Journal Year: 2019, Volume and Issue: 63, P. 102279 - 102279

Published: Sept. 28, 2019

Language: Английский

Citations

48
Design and Analysis of a Wearable Upper Limb Rehabilitation Robot with Characteristics of Tension Mechanism DOI Creative Commons
Zaixiang Pang, Tongyu Wang, Zhanli Wang

et al.

Applied Sciences, Journal Year: 2020, Volume and Issue: 10(6), P. 2101 - 2101

Published: March 20, 2020

Nowadays, patients with mild and moderate upper limb paralysis caused by cerebral apoplexy are uncomfortable autonomous rehabilitation. In this paper, according to the “rope + toothed belt” generalized rope drive design scheme, we a utility model for wearable rehabilitation robot tension mechanism. Owing study of human extremity anatomy, movement mechanisms, ranges motion, it can determine range motion angles arm joints, shoulder joint, elbow wrist joint separately under principle ensuring minimum driving torque. Then, kinematics, workspace dynamics analysis each structure performed. Finally, control system is designed. The experimental results show that convenient wear on body, robot’s freedom matches well body. It effectively support traction front rear arms affected limb, accurately transmit applied force joints. rationality verified, which help achieve training provide an effective equipment hemiplegia stroke.

Language: Английский

Citations

40
Development of Robot-Based Upper Limb Devices for Rehabilitation Purposes: a Systematic Review DOI
Jyotindra Narayan, Bhaben Kalita, Santosha K. Dwivedy

et al.

Augmented Human Research, Journal Year: 2021, Volume and Issue: 6(1)

Published: Jan. 12, 2021

Language: Английский

Citations

40
A robust adaptive-fuzzy-proportional-derivative controller for a rehabilitation lower limb exoskeleton DOI Creative Commons
Norazam Aliman, Rizauddin Ramli, Sallehuddin Mohamed Haris

et al.

Engineering Science and Technology an International Journal, Journal Year: 2022, Volume and Issue: 35, P. 101097 - 101097

Published: Feb. 11, 2022

Achieving high performance controller for multi-joints actuators on rehabilitation lower limb exoskeleton (RLLE) is difficult due to its non-linear characteristics. The with less tracking error a key challenge in their controller. Therefore, this paper presents new particle swarm optimization based initialization of model reference adaptive fuzzy logic proportional derivative (Adaptive-FLC-PD), used RLLE passive mode exercise. modelling, which integrates lower-limb coupled direct current motor as joint actuator and patient leg model, was simulated MATLAB. motion realised via trajectory method that imitates therapist-administered manual activity during passively An Adaptive-FLC-PD designed control the drive hip knee exoskeleton. stability analysis has been shown by applied Lyapunov function. compared (FLC) FLC-proportional (FLC-PD) algorithms. numerical ascertained designing, tuning simulating system RLLE.

Language: Английский

Citations

25
Neural Tracking Control of a Four-Wheeled Mobile Robot with Mecanum Wheels DOI Creative Commons
Mateusz Szeremeta, Marcin Szuster

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(11), P. 5322 - 5322

Published: May 24, 2022

This study designed an algorithm for the intelligent control of motion a mobile robot with mecanum wheels. After reviewing model kinematics and dynamics robot, we conducted synthesis neural to determine network weight adaptation, according Lyapunov stability theory. Using MATLAB/Simulink computing environment, developed numerical simulation implementation robot’s path parametric disturbances acting on object. To quality desired path, test motion, controlled use PD controller, was conducted. The proposed verified laboratory stand equipped dSpace DS1103 controller board Husarion Panther four-wheeled research confirmed improved by system.

Language: Английский

Citations

24
Implementation of an Upper-Limb Exoskeleton Robot Driven by Pneumatic Muscle Actuators for Rehabilitation DOI Creative Commons

Chun‐Ta Chen,

Wei-Yuan Lien,

Chun-Ting Chen

et al.

Actuators, Journal Year: 2020, Volume and Issue: 9(4), P. 106 - 106

Published: Oct. 20, 2020

Implementation of a prototype 4-degree freedom (4-DOF) upper-limb exoskeleton robot for rehabilitation was described in this paper. The proposed has three DOFs at the shoulder joint and one DOF elbow joint. is driven by pneumatic muscle actuators (PMA) via steel cables. To implement passive control, trajectories expressed Fourier series were first planned curve fitting. fuzzy sliding mode controller (FSMC) then applied to control. Several scenarios carried out validate designed PMA-actuated robot.

Language: Английский

Citations

38
Dynamic Modeling and Motion Control of a Cable-Driven Robotic Exoskeleton With Pneumatic Artificial Muscle Actuators DOI Creative Commons
Chun-Ta Chen, Wei-Yuan Lien, Chun-Ting Chen

et al.

IEEE Access, Journal Year: 2020, Volume and Issue: 8, P. 149796 - 149807

Published: Jan. 1, 2020

This paper presents the design, dynamic modeling and motion control of a novel cable-driven upper limb robotic exoskeleton for rehabilitation exercising. The proposed four degree-of-freedom exoskeleton, actuated by pneumatic artificial muscle actuators, is characterized safe, compact, lightweight structure, complying with an as close possible. In order to perform passive exercise, models were developed Lagrange formulation in terms quasi coordinates combined virtual work principle, then adaptive fuzzy sliding mode was designed trajectory control. Finally, experiments conducted validate prototype controller design.

Language: Английский

Citations

33