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Rehabilitation Robots: Design, Development, and Control
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Rehabilitation Robots: Design, Development, and Control

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 15352

Special Issue Editors

Dr. Brahim Brahmi

E-Mail Website
Guest Editor
Electrical Engineering Department, College Ahuntsic, Montreal, QC H2M 1Y8, Canada
Interests: nonlinear and adaptive control; bio-robotics; rehabilitation robots; industrial automation; IIoT; fundamental motion control concepts for nonholonomic/underactuated vehicle systems; haptic systems; intelligent and autonomous control of unmanned systems; intelligent systems; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad H. Rahman

E-Mail Website
Guest Editor
BioRobotics Lab, Mechanical/Biomedical Engineering Department, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
Interests: robotics; biomedical engineering; mechanical engineering; control systems; spinal cord injury rehabilitation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Age-related problems, including cardiovascular diseases such as stroke, are among the most common causes of disability worldwide. Stroke causes musculoskeletal disorders, including motor deficits in the upper and lower limbs. Rehabilitation therapies are considered the most effective treatment for promoting functional recovery. Rehabilitation robots constitute a novel technology that provides physiotherapy and motion aid to accelerate neuronal plasticity, measure patients' healing processes, and quantify sensory–motor action. Research on rehab robotics has considerably advanced throughout the last decade. Due to the complexity of the mechanical design (anthropomorphic design), the variety of assistance strategies (for different types of patients with varying degrees of impairments), and the sensitivity of their interaction with various human conditions, these robots remain an active area of study.

This Special Issue aims to feature cutting-edge research from the whole field of rehabilitation robotics, including novel design, development, and control of the exoskeleton/end-effector-type rehab robots, orthotics, and prosthetics for upper/lower limbs for applications of rehabilitation, power augmentation, and human–robot collaboration.

Dr. Brahim Brahmi
Dr. Mohammad H. Rahman
Guest Editors

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Published Papers (5 papers)

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Research

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14 pages, 10297 KiB  
Article
A Pneumatically Controlled Prosthetic Socket for Transfemoral Amputees
by Kang-Ho Lee, Hyun-Seok Heo, Jeongmin Kim, Jang Hyuk Cho, Kyoung Tae Kim, Jeong-Yong Hur, Jang Hwan Kim and Yongkoo Lee
Sensors 2024, 24(1), 133; https://doi.org/10.3390/s24010133 - 26 Dec 2023
Cited by 2 | Viewed by 2541
Abstract
Amputees typically experience changes in residual limb volume in their daily lives. It causes an uncomfortable fit of the socket by applying high pressure on the sensitive area of the residual limb or by loosening the socket. In this study, we developed a [...] Read more.
Amputees typically experience changes in residual limb volume in their daily lives. It causes an uncomfortable fit of the socket by applying high pressure on the sensitive area of the residual limb or by loosening the socket. In this study, we developed a transfemoral prosthetic socket for above-the-knee amputees that ensures a good socket fit by maintaining uniform and constant contact pressure despite volume changes in the residual limb. The socket has two air bladders in the posterior femoral region, and the pneumatic controller is located on the tibia of the prosthesis. The pneumatic system aims to minimize unstable fitting of the socket and improve walking performance by inflating or deflating the air bladder. The developed socket autonomously maintains the air pressure inside the prosthetic socket at a steady-state error of 3 mmHg or less by adjusting the amount of air in the air bladder via closed-loop control. In the clinical trial, amputee participants walked on flat and inclined surfaces. The displacement between the residual limb and socket during the gait cycle was reduced by up to 33.4% after air injection into the socket. The inflatable bladder increased the knee flexion angle on the affected side, resulting in increased stride length and gait velocity. The pneumatic socket provides a stable and comfortable walking experience not only when walking on flat ground but also on slopes. Full article
(This article belongs to the Special Issue Rehabilitation Robots: Design, Development, and Control)
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37 pages, 106303 KiB  
Article
The LIBRA NeuroLimb: Hybrid Real-Time Control and Mechatronic Design for Affordable Prosthetics in Developing Regions
by Alonso A. Cifuentes-Cuadros, Enzo Romero, Sebastian Caballa, Daniela Vega-Centeno and Dante A. Elias
Sensors 2024, 24(1), 70; https://doi.org/10.3390/s24010070 - 22 Dec 2023
Cited by 3 | Viewed by 3372
Abstract
Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and electronic prosthetics are being developed for individuals with this condition. Mechanics often require compensatory movements that can lead to awkward gestures. Electronic types are mainly controlled by superficial electromyography (sEMG). However, [...] Read more.
Globally, 2.5% of upper limb amputations are transhumeral, and both mechanical and electronic prosthetics are being developed for individuals with this condition. Mechanics often require compensatory movements that can lead to awkward gestures. Electronic types are mainly controlled by superficial electromyography (sEMG). However, in proximal amputations, the residual limb is utilized less frequently in daily activities. Muscle shortening increases with time and results in weakened sEMG readings. Therefore, sEMG-controlled models exhibit a low success rate in executing gestures. The LIBRA NeuroLimb prosthesis is introduced to address this problem. It features three active and four passive degrees of freedom (DOF), offers up to 8 h of operation, and employs a hybrid control system that combines sEMG and electroencephalography (EEG) signal classification. The sEMG and EEG classification models achieve up to 99% and 76% accuracy, respectively, enabling precise real-time control. The prosthesis can perform a grip within as little as 0.3 s, exerting up to 21.26 N of pinch force. Training and validation sessions were conducted with two volunteers. Assessed with the “AM-ULA” test, scores of 222 and 144 demonstrated the prosthesis’s potential to improve the user’s ability to perform daily activities. Future work will prioritize enhancing the mechanical strength, increasing active DOF, and refining real-world usability. Full article
(This article belongs to the Special Issue Rehabilitation Robots: Design, Development, and Control)
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23 pages, 1524 KiB  
Article
A Tube Model Predictive Control Method for Autonomous Lateral Vehicle Control Based on Sliding Mode Control
by Yong Dai and Duo Wang
Sensors 2023, 23(8), 3844; https://doi.org/10.3390/s23083844 - 9 Apr 2023
Cited by 3 | Viewed by 2691
Abstract
This paper aims to enhance the lateral path tracking control of autonomous vehicles (AV) in the presence of external disturbances. While AV technology has made significant strides, real-world driving scenarios often pose challenges such as slippery or uneven roads, which can adversely affect [...] Read more.
This paper aims to enhance the lateral path tracking control of autonomous vehicles (AV) in the presence of external disturbances. While AV technology has made significant strides, real-world driving scenarios often pose challenges such as slippery or uneven roads, which can adversely affect the lateral path tracking control and reduce driving safety and efficiency. Conventional control algorithms struggle to address this issue due to their inability to account for unmodeled uncertainties and external disturbances. To tackle this problem, this paper proposes a novel algorithm that combines robust sliding mode control (SMC) and tube model predictive control (MPC). The proposed algorithm leverages the strengths of both MPC and SMC. Specifically, MPC is used to derive the control law for the nominal system to track the desired trajectory. The error system is then employed to minimize the difference between the actual state and the nominal state. Finally, the sliding surface and reaching law of SMC are utilized to derive an auxiliary tube SMC control law, which helps the actual system keep up with the nominal system and achieve robustness. Experimental results demonstrate that the proposed method outperforms conventional tube MPC, linear quadratic regulator (LQR) algorithms, and MPC in terms of robustness and tracking accuracy, especially in the presence of unmodeled uncertainties and external disturbances. Full article
(This article belongs to the Special Issue Rehabilitation Robots: Design, Development, and Control)
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26 pages, 11943 KiB  
Article
Model-Based Control of a 4-DOF Rehabilitation Parallel Robot with Online Identification of the Gravitational Term
by Rafael J. Escarabajal, José L. Pulloquinga, Vicente Mata, Ángel Valera and Miguel Díaz-Rodríguez
Sensors 2023, 23(5), 2790; https://doi.org/10.3390/s23052790 - 3 Mar 2023
Cited by 1 | Viewed by 2070
Abstract
Parallel robots are being increasingly used as a fundamental component of lower-limb rehabilitation systems. During rehabilitation therapies, the parallel robot must interact with the patient, which raises several challenges to the control system: (1) The weight supported by the robot can vary from [...] Read more.
Parallel robots are being increasingly used as a fundamental component of lower-limb rehabilitation systems. During rehabilitation therapies, the parallel robot must interact with the patient, which raises several challenges to the control system: (1) The weight supported by the robot can vary from patient to patient, and even for the same patient, making standard model-based controllers unsuitable for those tasks since they rely on constant dynamic models and parameters. (2) The identification techniques usually consider the estimation of all dynamic parameters, bringing about challenges concerning robustness and complexity. This paper proposes the design and experimental validation of a model-based controller comprising a proportional-derivative controller with gravity compensation applied to a 4-DOF parallel robot for knee rehabilitation, where the gravitational forces are expressed in terms of relevant dynamic parameters. The identification of such parameters is possible by means of least squares methods. The proposed controller has been experimentally validated, holding the error stable following significant payload changes in terms of the weight of the patient’s leg. This novel controller allows us to perform both identification and control simultaneously and is easy to tune. Moreover, its parameters have an intuitive interpretation, contrary to a conventional adaptive controller. The performance of a conventional adaptive controller and the proposed one are compared experimentally. Full article
(This article belongs to the Special Issue Rehabilitation Robots: Design, Development, and Control)
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Review

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31 pages, 13059 KiB  
Review
Will Your Next Therapist Be a Robot?—A Review of the Advancements in Robotic Upper Extremity Rehabilitation
by Raouf Fareh, Ammar Elsabe, Mohammed Baziyad, Tunajjina Kawser, Brahim Brahmi and Mohammad H. Rahman
Sensors 2023, 23(11), 5054; https://doi.org/10.3390/s23115054 - 25 May 2023
Cited by 15 | Viewed by 3920
Abstract
Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of upper extremity injuries is viewed as [...] Read more.
Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of upper extremity injuries is viewed as a challenging problem due to the insufficient number of physiotherapists. With the recent advancements in technology, robots have been widely involved in upper extremity rehabilitation exercises. Although robotic technology and its involvement in the rehabilitation field are rapidly evolving, the literature lacks a recent review that addresses the updates in the robotic upper extremity rehabilitation field. Thus, this paper presents a comprehensive review of state-of-the-art robotic upper extremity rehabilitation solutions, with a detailed classification of various rehabilitative robots. The paper also reports some experimental robotic trials and their outcomes in clinics. Full article
(This article belongs to the Special Issue Rehabilitation Robots: Design, Development, and Control)
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