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Robotic Platforms for Assistance to People with Disabilities—Volume II

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

Deadline for manuscript submissions: closed (20 March 2024) | Viewed by 19136

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Special Issue Editors

Prof. Dr. Carlos A. Jara

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Guest Editor

HUman Robotics Group, Universitat d'Alacant, Alicante, Spain
Interests: design and robot simulation; robotic manipulation; human–robot interaction; assistive and rehabilitation robotics
Special Issues, Collections and Topics in MDPI journals

Dr. Juan Antonio Corrales Ramón

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Guest Editor

Singular Center for Research in Intelligent Technologies (CiTIUS), University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
Interests: human-robot interaction; robotic manipulation; multi-modal control; tactile sensing
Special Issues, Collections and Topics in MDPI journals

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.

Prof. Dr. Carlos A. Jara
Dr. Juan Antonio Corrales Ramón
Guest Editors

Manuscript Submission Information

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Keywords

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

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Published Papers (6 papers)

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Research

17 pages, 23713 KiB

Open AccessArticle

A Meal-Assistance Robot System for Asian Food and Its Food Acquisition Point Estimation and User Interface Based on Face Recognition

by Iksu Choi, KwangEun Ko, Hajun Song, Byung-Jin Jung, Jung-Hoon Hwang, Hyungpil Moon and Gi-Hun Yang

Appl. Sci. 2023, 13(5), 3216; https://doi.org/10.3390/app13053216 - 2 Mar 2023

Cited by 3 | Viewed by 3591

Abstract

Various meal-assistance robot (MAR) systems are being studied, and several products have already been commercialized to alleviate the imbalance between the rising demand and diminishing supply of meal care services. However, several challenges remain. First, most of these services can serve limited types of western food using a predefined route. Additionally, their spoon or fork sometimes makes it difficult to acquire Asian food that is easy to handle with chopsticks. In addition, their limited user interface, requiring physical contact, makes it difficult for people with severe disabilities to use MARs alone. This paper proposes an MAR system that is suitable for the diet of Asians who use chopsticks. This system uses Mask R-CNN to recognize the food area on the plate and estimates the acquisition points for each side dish. The points become target points for robot motion planning. Depending on which food the user selects, the robot uses chopsticks or a spoon to obtain the food. In addition, a non-contact user interface based on face recognition was developed for users with difficulty physically manipulating the interface. This interface can be operated on the user’s Android OS tablet without the need for a separate dedicated display. A series of experiments verified the proposed system’s effectiveness and feasibility. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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20 pages, 37205 KiB

Open AccessArticle

Intelligent Time Delay Control of Telepresence Robots Using Novel Deep Reinforcement Learning Algorithm to Interact with Patients

by Fawad Naseer, Muhammad Nasir Khan and Ali Altalbe

Appl. Sci. 2023, 13(4), 2462; https://doi.org/10.3390/app13042462 - 14 Feb 2023

Cited by 9 | Viewed by 2472

Abstract

Telepresence robots are gaining more popularity as a means of remote communication and human–robot interaction, allowing users to control and operate a physical robot remotely. However, controlling these robots can be challenging due to the inherent delays and latency in the communication systems. In this research paper, we propose a novel hybrid algorithm exploiting deep reinforcement learning (DRL) with a dueling double-deep Q-network (DDQN) and a gated recurrent unit (GRU) to assist and maneuver the telepresence robot during the delayed operating signals from the operator. The DDQN is used to learn the optimal control policy for the telepresence robot in a remote healthcare environment during delayed communication signals. In contrast, the GRU is employed to model the control signals’ temporal dependencies and handle the variable time delays in the communication system. The proposed hybrid approach is evaluated analytically and experimentally. The results demonstrate the approach’s effectiveness in improving telepresence robots’ tracking accuracy and stability performance. Multiple experiments show that the proposed technique depicts improved controlling efficiency with no guidance from the teleoperator. It can control and manage the operations of the telepresence robot during the delayed communication of 15 seconds by itself, which is 2.4% better than the existing approaches. Overall, the proposed hybrid approach demonstrates the potential implementation of RL and deep learning techniques in improving the control and stability of the telepresence robot during delayed operating signals from the operator. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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14 pages, 5764 KiB

Open AccessArticle

Modelling, Simulation and Performance Validation of the Pneumatic Actuation System of a Rehabilitation Device of the Human Hand Joints

by Ovidiu Filip, Andrea Deaconescu and Tudor Deaconescu

Appl. Sci. 2023, 13(3), 1649; https://doi.org/10.3390/app13031649 - 28 Jan 2023

Viewed by 1751

Abstract

The passive mobilization of the hand joints by means of dedicated equipment accelerates patient recovery and decreases significantly the costs of therapy. For this reason, research and development of such equipment is essential. Important reductions in the development cycle duration of such equipment can be achieved by means of a specific technique known as Model-Based Design. Starting from these considerations, this paper puts forward a Model-Based Design approach to the study of a new concept of rehabilitation equipment of the hand joints actuated by a pneumatic muscle. The originality of the paper consists in the MATLAB-based rendering of the functional model of the rehabilitation equipment actuation system and in the presented simulation results. The purpose of this research was to obtain information concerning the behavior of the proposed system and to predict its performance prior to it being built physically. After simulation, the results are compared to the operational performance of the experimental model. The conclusion shows that the proposed operational model describes accurately the actual behavior of the system and can be used for future optimization of the rehabilitation equipment. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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20 pages, 10188 KiB

Open AccessArticle

Assistive Robot with an AI-Based Application for the Reinforcement of Activities of Daily Living: Technical Validation with Users Affected by Neurodevelopmental Disorders

by Nadia Nasri, Roberto J. López-Sastre, Soraya Pacheco-da-Costa, Iván Fernández-Munilla, Carlos Gutiérrez-Álvarez, Thais Pousada-García, Francisco Javier Acevedo-Rodríguez and Saturnino Maldonado-Bascón

Appl. Sci. 2022, 12(19), 9566; https://doi.org/10.3390/app12199566 - 23 Sep 2022

Cited by 4 | Viewed by 2364

Abstract

In this work, we propose the first study of a technical validation of an assistive robotic platform, which has been designed to assist people with neurodevelopmental disorders. The platform is called LOLA2 and it is equipped with an artificial intelligence-based application to reinforce the learning of daily life activities in people with neurodevelopmental problems. LOLA2 has been integrated with an ROS-based navigation system and a user interface for healthcare professionals and their patients to interact with it. Technically, we have been able to embed all these modules into an NVIDIA Jetson Xavier board, as well as an artificial intelligence agent for online action detection (OAD). This OAD approach provides a detailed report on the degree of performance of a set of daily life activities that are being learned or reinforced by users. All the human–robot interaction process to work with users with neurodevelopmental disorders has been designed by a multidisciplinary team. Among its main features are the ability to control the robot with a joystick, a graphical user interface application that shows video tutorials with the activities to reinforce or learn, and the ability to monitor the progress of the users as they complete tasks. The main objective of the assistive robotic platform LOLA2 is to provide a system that allows therapists to track how well the users understand and perform daily tasks. This paper focuses on the technical validation of the proposed platform and its application. To do so, we have carried out a set of tests with four users with neurodevelopmental problems and special physical conditions under the supervision of the corresponding therapeutic personnel. We present detailed results of all interventions with end users, analyzing the usability, effectiveness, and limitations of the proposed technology. During its initial technical validation with real users, LOLA2 was able to detect the actions of users with disabilities with high precision. It was able to distinguish four assigned daily actions with high accuracy, but some actions were more challenging due to the physical limitations of the users. Generally, the presence of the robot in the therapy sessions received excellent feedback from medical professionals as well as patients. Overall, this study demonstrates that our developed robot is capable of assisting and monitoring people with neurodevelopmental disorders in performing their daily living tasks. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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25 pages, 15562 KiB

Open AccessArticle

A Wheels-on-Knees Quadruped Assistive Robot to Carry Loads

by Wujing Li, Linchao Wei and Xiaochen Zhang

Appl. Sci. 2022, 12(18), 9239; https://doi.org/10.3390/app12189239 - 15 Sep 2022

Cited by 3 | Viewed by 3829

Abstract

This work introduces a high-performance, quadruped-assistive-robot expandable platform with wheel–leg mode transformation functions. The robot platform is designed for transporting goods in residential areas such as apartments, private houses, and office buildings. It is capable to move fast on flat ground on wheels or use legs to move in other places, especially for moving on and off residential staircases and wheelchair accessible ramps. To achieve higher load capacity and combine the knee joint with the drive wheel, we designed a compact torso–leg structure, driving the lower link through a ligament-like structure. Because the distance between the wheel and the torso is short, the mass centroid drops and the force arm caused by the load is reduced; the designed sample robot is capable to transport uniform mass loads up to 15 kg while keeping it affordable. The proposed ligament-like transmission structure also ensures the torso’s even gesture and load capability in its walking mode. Gait motion planning, finite element analysis, and task-oriented simulation have been conducted to prove its applicability and feasibility when given a heavy load to transport across flat and staired scenarios. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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13 pages, 2124 KiB

Open AccessArticle

Regulating Grip Forces through EMG-Controlled Protheses for Transradial Amputees

by Irati Rasines, Miguel Prada, Viacheslav Bobrov, Dhruv Agrawal, Leire Martinez, Pedro Iriondo, Anthony Remazeilles and Joseph McIntyre

Appl. Sci. 2021, 11(23), 11199; https://doi.org/10.3390/app112311199 - 25 Nov 2021

Viewed by 3453

Abstract

This study aims to evaluate different combinations of features and algorithms to be used in the control of a prosthetic hand wherein both the configuration of the fingers and the gripping forces can be controlled. This requires identifying machine learning algorithms and feature sets to detect both intended force variation and hand gestures in EMG signals recorded from upper-limb amputees. However, despite the decades of research into pattern recognition techniques, each new problem requires researchers to find a suitable classification algorithm, as there is no such thing as a universal ’best’ solution. Consideration of different techniques and data representation represents a fundamental practice in order to achieve maximally effective results. To this end, we employ a publicly-available database recorded from amputees to evaluate different combinations of features and classifiers. Analysis of data from 9 different individuals shows that both for classic features and for time-dependent power spectrum descriptors (TD-PSD) the proposed logarithmically scaled version of the current window plus previous window achieves the highest classification accuracy. Using linear discriminant analysis (LDA) as a classifier and applying a majority-voting strategy to stabilize the individual window classification, we obtain 88% accuracy with classic features and 89% with TD-PSD features. Full article

(This article belongs to the Special Issue Robotic Platforms for Assistance to People with Disabilities—Volume II)

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