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Technologies
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Assistive Robotics
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Assistive Robotics

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Assistive Technologies".

Deadline for manuscript submissions: closed (29 June 2018) | Viewed by 32216

Special Issue Editors

Dr. Byung-Cheol Min

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907, USA
Interests: robotics; multi-robot systems; human-robot interaction; field robotics; assistive robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Ramviyas Parasuraman

E-Mail Website
Guest Editor
Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907 USA
Interests: search and rescue robots; human–root interaction; assistive robotics; and communication-aware motion planning; sensing; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As robot technology evolves to a level at which robots can interact with humans in their daily lives, they must be able to interact equally with people of varying abilities. Assistive Robotics is a branch of robotics which focuses on providing sensory and perception abilities and performs actions that are beneficial to the elderly and physically challenged people. This Special Issue will present the recent research advances in the field of assistive robotics that can empower people to increase independence and improve overall quality of life. Robots for the visually impaired, telepresence robots for physical impairments, social robots for cognitive impairments, and wearable robots are some of the areas of interest in this Special Issue.

We welcome original research papers that focus on fundamental research as well as experimental research on the theme of Assistive Robotics. Survey papers or tutorial papers on this topic are also encouraged.

Dr. Byung-Cheol Min
Dr. Ramviyas Parasuraman
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Technologies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 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 robot technologies for the elderly
  • autonomous wheelchair navigation/assistance
  • navigation aids for people who are visually impaired
  • social robots for children with autism
  • telepresence robot for remote interaction
  • prosthetic hands
  • multi-robot teams for people with disabilities
  • automated manipulation systems
  • autonomous robot companions
  • wearable robots and devices
  • human-robot interaction
  • qualitative user studies and methods in assistive robotics

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Published Papers (5 papers)

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Editorial

Jump to: Research

2 pages, 147 KiB  
Editorial
Special Issue on “Assistive Robotics”
by Ramviyas Parasuraman and Byung-Cheol Min
Technologies 2018, 6(4), 95; https://doi.org/10.3390/technologies6040095 - 20 Oct 2018
Viewed by 4164
Abstract
The technology behind robotics has rapidly advanced to a level enabling humans and robots to interact in everyday aspects of life. [...] Full article
(This article belongs to the Special Issue Assistive Robotics)

Research

Jump to: Editorial

17 pages, 714 KiB  
Article
Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training
by Konstantinos Tsiakas, Maher Abujelala and Fillia Makedon
Technologies 2018, 6(2), 49; https://doi.org/10.3390/technologies6020049 - 14 May 2018
Cited by 47 | Viewed by 7255
Abstract
Socially-Assistive Robotics (SAR) has been extensively used for a variety of applications, including educational assistants, exercise coaches and training task instructors. The main goal of such systems is to provide a personalized and tailored session that matches user abilities and needs. While objective [...] Read more.
Socially-Assistive Robotics (SAR) has been extensively used for a variety of applications, including educational assistants, exercise coaches and training task instructors. The main goal of such systems is to provide a personalized and tailored session that matches user abilities and needs. While objective measures (e.g., task performance) can be used to adjust task parameters (e.g., task difficulty), towards personalization, it is essential that such systems also monitor task engagement to personalize their training strategies and maximize the effects of the training session. We propose an Interactive Reinforcement Learning (IRL) framework that combines explicit feedback (task performance) with implicit human-generated feedback (task engagement) to achieve efficient personalization. We illustrate the framework with a cognitive training task, describing our data-driven methodology (data collection and analysis, user simulation) towards designing our proposed real-time system. Our data analysis and the reinforcement learning experiments on real user data indicate that the integration of task engagement as human-generated feedback in the RL mechanism can facilitate robot personalization, towards a real-time personalized robot-assisted training system. Full article
(This article belongs to the Special Issue Assistive Robotics)
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15 pages, 1582 KiB  
Article
Tactile Myography: An Off-Line Assessment of Able-Bodied Subjects and One Upper-Limb Amputee
by Claudio Castellini, Risto Kõiva, Cristian Pasluosta, Carla Viegas and Björn M. Eskofier
Technologies 2018, 6(2), 38; https://doi.org/10.3390/technologies6020038 - 23 Mar 2018
Cited by 12 | Viewed by 6074
Abstract
Human-machine interfaces to control prosthetic devices still suffer from scarce dexterity and low reliability; for this reason, the community of assistive robotics is exploring novel solutions to the problem of myocontrol. In this work, we present experimental results pointing in the direction that [...] Read more.
Human-machine interfaces to control prosthetic devices still suffer from scarce dexterity and low reliability; for this reason, the community of assistive robotics is exploring novel solutions to the problem of myocontrol. In this work, we present experimental results pointing in the direction that one such method, namely Tactile Myography (TMG), can improve the situation. In particular, we use a shape-conformable high-resolution tactile bracelet wrapped around the forearm/residual limb to discriminate several wrist and finger activations performed by able-bodied subjects and a trans-radial amputee. Several combinations of features/classifiers were tested to discriminate among the activations. The balanced accuracy obtained by the best classifier/feature combination was on average 89.15% (able-bodied subjects) and 88.72% (amputated subject); when considering wrist activations only, the results were on average 98.44% for the able-bodied subjects and 98.72% for the amputee. The results obtained from the amputee were comparable to those obtained by the able-bodied subjects. This suggests that TMG is a viable technique for myoprosthetic control, either as a replacement of or as a companion to traditional surface electromyography. Full article
(This article belongs to the Special Issue Assistive Robotics)
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11 pages, 198 KiB  
Article
Assistant without Master? Some Conceptual Implications of Assistive Robotics in Health Care
by Bettina-Johanna Krings and Nora Weinberger
Technologies 2018, 6(1), 13; https://doi.org/10.3390/technologies6010013 - 18 Jan 2018
Cited by 10 | Viewed by 5793
Abstract
The subject of “technical assistants” in inpatient care is currently being widely discussed in scientific and public circles. In many cases, though, it has become apparent that the umbrella term “assistive technologies”, also in the context of robotics, is very contrived. Against this [...] Read more.
The subject of “technical assistants” in inpatient care is currently being widely discussed in scientific and public circles. In many cases, though, it has become apparent that the umbrella term “assistive technologies”, also in the context of robotics, is very contrived. Against this background, the authors of this article reflect on the meaning of “assistance” in socio-technical systems, and critically review its relevance. To understand and demonstrate “assistive” functions, it is essential to establish a frame of reference. The re-evaluation of an empirical study of people with dementia in inpatient care has revealed the functional character of technical assistance systems. The results, however, show that the theoretical debate on the social and organisational function of “assistance” in these technical fields is still lacking. Therefore, the reflections in this paper may also provide some starting points for this debate. Full article
(This article belongs to the Special Issue Assistive Robotics)
3971 KiB  
Article
Combining Electromyography and Tactile Myography to Improve Hand and Wrist Activity Detection in Prostheses
by Noémie Jaquier, Mathilde Connan, Claudio Castellini and Sylvain Calinon
Technologies 2017, 5(4), 64; https://doi.org/10.3390/technologies5040064 - 6 Oct 2017
Cited by 10 | Viewed by 7261
Abstract
Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the application of regression to muscle activity, detected using a [...] Read more.
Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the application of regression to muscle activity, detected using a flexible tactile sensor recording muscle bulging in the forearm (tactile myography—TMG). The sensor is made of 320 highly sensitive cells organized in an array forming a bracelet. We propose the use of Gaussian process regression to improve the prediction of wrist, hand and single-finger activation, using TMG, surface electromyography (sEMG; the traditional approach in the field), and a combination of the two. We prove the effectiveness of the approach for different levels of activations in a real-time goal-reaching experiment using tactile data. Furthermore, we performed a batch comparison between the different forms of sensorization, using a Gaussian process with different kernel distances. Full article
(This article belongs to the Special Issue Assistive Robotics)
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