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Robotic and Sensor Technology for Upper Limb Rehabilitation

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 21714

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Special Issue Editors

Dr. Marco Germanotta

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Guest Editor

IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
Interests: rehabilitation; robotics; biomechanics; gait analysis; movement analysis; musculoskeletal disorders; postural balance; motor learning; neurorehabilitation

Dr. Michela Goffredo

E-Mail Website
Guest Editor

IRCCS San Raffaele Pisana, Rome, Italy
Interests: rehabilitation; robotics; biomechanics; gait analysis; movement analysis; musculoskeletal disorders; postural balance; motor learning; neurorehabilitation

Dr. Eduardo Palermo

E-Mail Website
Guest Editor

Department of Mechanical and Aerospace Engineering, SAPIENZA University of Rome, 00184 Rome, Italy
Interests: experimental mechanics; robotic rehabilitation; biomedical and biomechanical measurements
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last two decades, a considerable effort has been devoted to developing rehabilitation robots, aimed at supporting recovery from sensorimotor deficits, experienced by individuals after central nervous system damage, with a particular focus on stroke. Today, thanks to technological advancements and cost reduction, these devices are being increasingly employed in clinical practice.

Rehabilitation robots can provide tailored therapies that fulfill the main principles of neurorehabilitation, i.e., repetition, high intensity, and task specificity, in a complex and enriched environment, reducing, at the same time, the physical burden on therapists. According to the abovementioned principles, robotic rehabilitation aims to promote neuroplasticity and, therefore, neurophysiological recovery, inducing functional or structural plasticity in brain networks, controlling both motor and cognitive functions.

Along with their use as rehabilitation tools, these devices can also act as evaluation instruments, to quantify the motor performance of patients. In fact, thanks their built-in sensing technology, they allow evaluating kinematic and kinetic data. Such information is then processed to obtain quantitative parameters for tracking patient progress during robot-assisted rehabilitation, and to design patient-tailored rehabilitation protocols.

This Special Issue aims to cover all these aspects, with a special focus on improvements in mechanical design and control of robotic devices, robotic assessment of sensorimotor function, neurophysiological mechanisms implied in robotic rehabilitation, and translational research of efficacy and/or cost-effectiveness of robotic rehabilitation.

Dr. Marco Germanotta
Dr. Michela Goffredo
Dr. Eduardo Palermo
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

Rehabilitation robotics
Robotic assessment
Robot-assisted therapy
Robot design
Robot control
Robot-aided cognitive rehabilitation
Robotics for neurorehabilitation
Brain–machine interface in neurorehabilitation
Neurological rehabilitation
Neural processes of rehabilitation
Rehabilitation neurophysiology
Stroke rehabilitation
Computational neurorehabilitation

Published Papers (5 papers)

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Research

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24 pages, 6119 KiB

Open AccessArticle

An Assist-as-Needed Controller for Passive, Assistant, Active, and Resistive Robot-Aided Rehabilitation Training of the Upper Extremity

by Leigang Zhang, Shuai Guo and Qing Sun

Appl. Sci. 2021, 11(1), 340; https://doi.org/10.3390/app11010340 - 31 Dec 2020

Cited by 25 | Viewed by 3271

Abstract

Clinical studies have demonstrated that robot-involved therapy can effectively improve the rehabilitation training effect of motor ability and daily behavior ability of subjects with an upper limb motor dysfunction. This paper presents an impedance-based assist-as-needed controller that can be used in robot-aided rehabilitation training for subjects with an upper extremity dysfunction. Then, the controller is implemented on an end-effector upper extremity rehabilitation robot which could assist subjects in performing training with a spatial trajectory. The proposed controller enables subjects’ arms to have motion freedom by building a fault-tolerant region around the rehabilitation trajectory. Subjects could move their upper limb without any assistance within the fault-tolerant region while the robot would provide assistance according to the subjects’ functional ability when deviating from the fault-tolerant region. Besides, we also put forward the stiffness field around the fault-tolerant region to increase the robot’s assistance when subjects’ hand is moving outside the fault-tolerant region. A series of columnar rigid walls would be constructed in the controller according to the subjects’ functional ability, and the stiffness of the wall increases as the motion performance deteriorates. Furthermore, the controller contains five adjustable parameters. The controller would show different performances by adjusting these parameters and satisfy the requirement of robot-aided rehabilitation training at different rehabilitation stages such as passive, assistant, active, and resistant training. Finally, the controller was tested with an elderly female participant with different controller parameters, and experimental results verified the correctness of the controller and its potential ability to satisfy the training requirements at different rehabilitation stages. In the close future, the proposed controller in this work is planned to be applied on more subjects and also patients who have upper limb motor dysfunctions to demonstrate performance of the controller with different parameters. Full article

(This article belongs to the Special Issue Robotic and Sensor Technology for Upper Limb Rehabilitation)

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14 pages, 639 KiB

Open AccessArticle

Switched Control of Motor Assistance and Functional Electrical Stimulation for Biceps Curls

by Courtney Rouse, Brendon Allen and Warren Dixon

Appl. Sci. 2020, 10(22), 8090; https://doi.org/10.3390/app10228090 - 15 Nov 2020

Cited by 3 | Viewed by 1731

Abstract

Rehabilitation robotics is an emerging tool for motor recovery from various neurological impairments. However, balancing the human and robot contribution is an open problem. While the motor input can reduce fatigue, which is often a limiting factor of functional electrical stimulation (FES) exercises, too much assistance can slow progress. For a person with a neurological impairment, FES can assist by strategically contracting their muscle(s) to achieve a desired limb movement; however, feasibility can be limited due to factors such as subject comfort, muscle mass, unnatural muscle fiber recruitment, and stimulation saturation. Thus, motor assistance in addition to FES can be useful for prolonging exercise while still ensuring physical effort from the person. In this paper, FES is applied to the biceps brachii to perform biceps curls, and motor assistance is applied intermittently whenever the FES input reaches a pre-set comfort threshold. Exponential stability of the human–robot system is proven with a Lyapunov-like switched systems stability analysis. Experimental results from participants with neurological conditions demonstrate the feasibility and performance of the controller. Full article

(This article belongs to the Special Issue Robotic and Sensor Technology for Upper Limb Rehabilitation)

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18 pages, 5214 KiB

Open AccessArticle

Development and Assist-As-Needed Control of an End-Effector Upper Limb Rehabilitation Robot

by Leigang Zhang, Shuai Guo and Qing Sun

Appl. Sci. 2020, 10(19), 6684; https://doi.org/10.3390/app10196684 - 24 Sep 2020

Cited by 52 | Viewed by 5459

Abstract

Robot-assisted rehabilitation therapy has been proven to effectively improve upper limb motor function and daily behavior of patients with motor dysfunction, and the demand has increased at every stage of the rehabilitation recovery. According to the motor relearning program theory, upper limb motor dysfunction can be restored by a certain amount of repetitive training. Robotics devices can be an approach to accelerate the rehabilitation process by maximizing the patients’ training intensity. This paper develops a new end-effector upper limb rehabilitation robot (EULRR) first and then presents a controller that is suitable for the assist-as-needed (AAN) training of the patients when performing the rehabilitation training. The AAN controller is a strategy that helps the patient’s arm to stay close to the given trajectory while allowing for spatial freedom. This controller enables the patient’s arm to have spatial freedom by constructing a virtual channel around the predetermined training trajectory. Patients could move their arm freely in the allowed virtual channel during rehabilitation training while the robot provides assistance when deviating from the virtual channel. The AAN controller is preliminarily tested with a healthy male subject in different conditions based on the EULRR. The experimental results demonstrate that the proposed AAN controller could provide assistance when moving out of the virtual channel and provide no assistance when moving along the trajectory within the virtual channel. In the close future, the controller is planned to be used in elderly volunteers and help to increase the intensity of the rehabilitation therapy by assisting the arm movement and by provoking active participation. Full article

(This article belongs to the Special Issue Robotic and Sensor Technology for Upper Limb Rehabilitation)

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15 pages, 7066 KiB

Open AccessArticle

Shoulder Kinematics Assessment towards Exoskeleton Development

by Pablo Delgado, Sajja Alekhya, Amirhossein Majidirad, Nils A. Hakansson, Jaydip Desai and Yimesker Yihun

Appl. Sci. 2020, 10(18), 6336; https://doi.org/10.3390/app10186336 - 11 Sep 2020

Cited by 12 | Viewed by 4643

Abstract

Neuromuscular and sensorimotor degeneration caused by stroke or any other disease significantly reduce the physical, cognitive, and social well-being across the life span. Mostly, therapeutic interventions are employed in order to restore the lost degrees-of-freedom (DOF) caused by such impairments and automating these therapeutic tasks through exoskeletons/robots is becoming a common practice. However, aligning these robotic devices with the complex anatomical and geometrical motions of the joints is very challenging. At the same time, a good alignment is required in order to establish a better synergy of human-exoskeleton system for an effective intervention procedure. In this paper, a case study of an exoskeleton and shoulder joint alignment were studied through different size and orientation impairment models through motion capture data and musculoskeletal modeling in OpenSim. A preliminary result indicates that shoulder elevation is very sensitive to misalignment and varies with shoulder joint axes orientation; this is partly due to drastic displacement of the upper arm axes with respect to the shoulder joint origin during elevation. Additional study and analysis is required to learn any possible restraint on shoulder elevation that could potentially help in the exoskeleton development. Full article

(This article belongs to the Special Issue Robotic and Sensor Technology for Upper Limb Rehabilitation)

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Review

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22 pages, 1005 KiB

Open AccessReview

Upper Limb Bionic Orthoses: General Overview and Forecasting Changes

by Gustaw Rzyman, Jacek Szkopek, Grzegorz Redlarski and Aleksander Palkowski

Appl. Sci. 2020, 10(15), 5323; https://doi.org/10.3390/app10155323 - 31 Jul 2020

Cited by 8 | Viewed by 5824

Abstract

Using robotics in modern medicine is slowly becoming a common practice. However, there are still important life science fields which are currently devoid of such advanced technology. A noteworthy example of a life sciences field which would benefit from process automation and advanced robotic technology is rehabilitation of the upper limb with the use of an orthosis. Here, we present the state-of-the-art and prospects for development of mechanical design, actuator technology, control systems, sensor systems, and machine learning methods in rehabilitation engineering. Moreover, current technical solutions, as well as forecasts on improvement, for exoskeletons are presented and reviewed. The overview presented might be the cornerstone for future research on advanced rehabilitation engineering technology, such as an upper limb bionic orthosis. Full article

(This article belongs to the Special Issue Robotic and Sensor Technology for Upper Limb Rehabilitation)

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