Special Issue "Assistive Robotics"

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

Deadline for manuscript submissions: 30 April 2018

Special Issue Editors

Guest Editor
Dr. Byung-Cheol Min

Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907 USA
Website | E-Mail
Phone: +1 765 586 5944
Interests: robotics; human–robot interaction; multi-robot systems; assistive robotics; sensor networks
Guest Editor
Dr. Ramviyas Parasuraman

Department of Computer and Information Technology, Purdue University, West Lafayette, IN 47907 USA
Website | E-Mail
Interests: search and rescue robots; human–root interaction; assistive robotics; and communication-aware motion planning; sensing; machine learning

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 papers will be 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 quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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

Published Papers (1 paper)

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Research

Open AccessArticle Combining Electromyography and Tactile Myography to Improve Hand and Wrist Activity Detection in Prostheses
Technologies 2017, 5(4), 64; doi:10.3390/technologies5040064
Received: 15 August 2017 / Revised: 29 September 2017 / Accepted: 2 October 2017 / Published: 6 October 2017
PDF Full-text (3971 KB) | HTML Full-text | XML Full-text | Supplementary Files
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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