Special Issue "Robotic Platforms for Assistance to People with Disabilities"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (28 February 2021).

Special Issue Editors

Prof. Dr. Carlos A. Jara
E-Mail Website
Guest Editor
Human Robotics Group, University of Alicante, 03690 Alicante, Spain
Interests: assistive robotics; human-robot interaction; design and control of robots
Special Issues and Collections in MDPI journals
Dr. Juan Antonio Corrales Ramón
E-Mail Website
Guest Editor
SIGMA Clermont, Institut Pascal, Aubiere, France
Interests: human-robot interaction; robotic manipulation; multi-modal control; tactile sensing

Special Issue Information

Dear colleagues,

People with congenital and/or acquired disabilities form a significant number of dependents in the current society. These patients lack enough autonomy to live an independent life. Robotic platforms for providing assistance to people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance in improving their quality of life, mainly applied to people who have mobility problems or some type of functional disability. The impact and capacity of assistance of collaborative robotics in this area has continuously improved the healthcare world in aspects such as chronic disease prevention, saving time for professionals, and lower spending for public health. In this sense, an important aspect to emphasize in these robotic assistance environments is the human–robot interaction. This topic demands sensitive and intelligent robotics platforms, equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms.

The Special Issue of Applied Sciences “Robotic Platforms for Assistance to People with Disabilities” aims to cover recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. Papers should address innovative solutions in this field, including affordable assistive robotics devices, new techniques in control/computer vision for intelligent and safe human–robot interaction, exoskeletons or exosuits to assist people with mobility problems, and advances in mobile manipulators for assistive tasks.

Some topics include but are not limited to:

Assistive robots for people with disabilities in daily or clinical environments;

Human–robot interaction techniques for assistive environments;

Computer vision and control for human–robot physical interaction;

Interaction-aware motion planning with disabled people;

Exoskeletons or exosoft solutions for assistance;

Mobile manipulators for assistive tasks.

Dr. Carlos Alberto Jara
Dr. Juan Antonio Corrales Ramón
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 2000 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

  • assistive robots for disabled people
  • human–robot interaction
  • assistive robotic exoskeletons or soft exosuits
  • assistive mobile manipulators
  • user-centered design of robotic platforms

Published Papers (5 papers)

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Research

Open AccessArticle
Human Pose Detection for Robotic-Assisted and Rehabilitation Environments
Appl. Sci. 2021, 11(9), 4183; https://doi.org/10.3390/app11094183 - 04 May 2021
Viewed by 258
Abstract
Assistance and rehabilitation robotic platforms must have precise sensory systems for human–robot interaction. Therefore, human pose estimation is a current topic of research, especially for the safety of human–robot collaboration and the evaluation of human biomarkers. Within this field of research, the evaluation [...] Read more.
Assistance and rehabilitation robotic platforms must have precise sensory systems for human–robot interaction. Therefore, human pose estimation is a current topic of research, especially for the safety of human–robot collaboration and the evaluation of human biomarkers. Within this field of research, the evaluation of the low-cost marker-less human pose estimators of OpenPose and Detectron 2 has received much attention for their diversity of applications, such as surveillance, sports, videogames, and assessment in human motor rehabilitation. This work aimed to evaluate and compare the angles in the elbow and shoulder joints estimated by OpenPose and Detectron 2 during four typical upper-limb rehabilitation exercises: elbow side flexion, elbow flexion, shoulder extension, and shoulder abduction. A setup of two Kinect 2 RGBD cameras was used to obtain the ground truth of the joint and skeleton estimations during the different exercises. Finally, we provided a numerical comparison (RMSE and MAE) among the angle measurements obtained with OpenPose, Detectron 2, and the ground truth. The results showed how OpenPose outperforms Detectron 2 in these types of applications. Full article
(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities)
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Open AccessFeature PaperArticle
A BMI Based on Motor Imagery and Attention for Commanding a Lower-Limb Robotic Exoskeleton: A Case Study
Appl. Sci. 2021, 11(9), 4106; https://doi.org/10.3390/app11094106 - 30 Apr 2021
Viewed by 312
Abstract
Lower-limb robotic exoskeletons are wearable devices that can be beneficial for people with lower-extremity motor impairment because they can be valuable in rehabilitation or assistance. These devices can be controlled mentally by means of brain–machine interfaces (BMI). The aim of the present study [...] Read more.
Lower-limb robotic exoskeletons are wearable devices that can be beneficial for people with lower-extremity motor impairment because they can be valuable in rehabilitation or assistance. These devices can be controlled mentally by means of brain–machine interfaces (BMI). The aim of the present study was the design of a BMI based on motor imagery (MI) to control the gait of a lower-limb exoskeleton. The evaluation is carried out with able-bodied subjects as a preliminary study since potential users are people with motor limitations. The proposed control works as a state machine, i.e., the decoding algorithm is different to start (standing still) and to stop (walking). The BMI combines two different paradigms for reducing the false triggering rate (when the BMI identifies irrelevant brain tasks as MI), one based on motor imagery and another one based on the attention to the gait of the user. Research was divided into two parts. First, during the training phase, results showed an average accuracy of 68.44 ± 8.46% for the MI paradigm and 65.45 ± 5.53% for the attention paradigm. Then, during the test phase, the exoskeleton was controlled by the BMI and the average performance was 64.50 ± 10.66%, with very few false positives. Participants completed various sessions and there was a significant improvement over time. These results indicate that, after several sessions, the developed system may be employed for controlling a lower-limb exoskeleton, which could benefit people with motor impairment as an assistance device and/or as a therapeutic approach with very limited false activations. Full article
(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities)
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Open AccessArticle
Exoscarne: Assistive Strategies for an Industrial Meat Cutting System Based on Physical Human-Robot Interaction
Appl. Sci. 2021, 11(9), 3907; https://doi.org/10.3390/app11093907 - 26 Apr 2021
Viewed by 254
Abstract
Musculoskeletal disorders of the wrist are common in the meat industry. A proof of concept of a physical human-robot interaction (pHRI)-based assistive strategy for an industrial meat cutting system is demonstrated which can be transferred to an exoskeleton later. We discuss how a [...] Read more.
Musculoskeletal disorders of the wrist are common in the meat industry. A proof of concept of a physical human-robot interaction (pHRI)-based assistive strategy for an industrial meat cutting system is demonstrated which can be transferred to an exoskeleton later. We discuss how a robot can assist a human in pHRI, specifically in the context of an industrial project i.e for the meat cutting industry. We developed an impedance control-based system that enables a KUKA LWR robot to provide assistive forces to a professional butcher while simultaneously allowing motion of the knife (tool) in all degrees of freedom. We developed two assistive strategies—a force amplification strategy and an intent prediction strategy—and integrated them into an impedance controller. Full article
(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities)
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Open AccessArticle
A Hand Motor Skills Rehabilitation for the Injured Implemented on a Social Robot
Appl. Sci. 2021, 11(7), 2943; https://doi.org/10.3390/app11072943 - 25 Mar 2021
Viewed by 340
Abstract
In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the [...] Read more.
In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the rehabilitation plan. Our system takes advantage of a low-cost hand-tracking device to provide a quantitative analysis of the performance of the patient. It also integrates a low-cost surface electromyography (sEMG) sensor in order to provide insight about which muscles are being activated while completing the exercises. It is also modular and can be deployed on a social robot. We tested our proposal in two different facilities for rehabilitation with high success. The therapists and patients felt more motivation while using HaReS, which improved the adherence to the rehabilitation plan. In addition, the therapists were able to provide services to more patients than when they used their traditional methodology. Full article
(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities)
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Open AccessArticle
Intelligent Monitoring Platform to Evaluate the Overall State of People with Neurological Disorders
Appl. Sci. 2021, 11(6), 2789; https://doi.org/10.3390/app11062789 - 20 Mar 2021
Viewed by 337
Abstract
The percentage of people around the world who are living with some kind of disability or disorder has increased in recent years and continues to rise due to the aging of the population and the increase in chronic health disorders. People with disabilities [...] Read more.
The percentage of people around the world who are living with some kind of disability or disorder has increased in recent years and continues to rise due to the aging of the population and the increase in chronic health disorders. People with disabilities find problems in performing some of the activities of daily life, such as working, attending school, or participating in social and recreational events. Neurological disorders such as epilepsy, learning disabilities, autism spectrum disorder, or Alzheimer’s, are among the main diseases that affect a large number of this population. However, thanks to the assistive technologies (AT), these people can improve their performance in some of the obstacles presented by their disorders. This paper presents a new system that aims to help people with neurological disorders providing useful information about their pathologies. This novelty system consists of a platform where the physiological and environmental data acquisition, the feature engineering, and the machine learning algorithms are combined to generate customs predictive models that help the user. Finally, to demonstrate the use of the system and the working methodology employed in the platform, a simple example case is presented. This example case carries out an experimentation that presents a user without neurological problems that shows the versatility of the platform and validates that it is possible to get useful information that can feed an intelligent algorithm. Full article
(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities)
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