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Hybrid Human-Machine Interfaces for Robot-Aided Rehabilitation and Assistance

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 May 2023) | Viewed by 2233

Special Issue Editors

Department of Information Engineering, University of Padova, 35131 Padova, Italy
Interests: computational neuroscience; cognitive, affective, and behavioral neuroscience; circuits and cellular neuroscience; multimodal neuroimaging and analysis methods

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Guest Editor
Department of Information Engineering, University of Padova, 35131 Padova, Italy
Interests: rehabilitation robotics; exoskeleton robotics; electromyograph; neurorehabilitation; brain-computer interfaces; robotics

Special Issue Information

Dear Colleagues,

An extensive body literature has demonstrated the benefits of using advanced robots for mediating rehabilitation therapy. Some of these robotic devices also have the potential for use at home by patients to provide daily assistance. In the last few years, a greater interest has been shown in interfacing the patient to these devices by means of neurophysiological signals extracted at different levels of the neuromuscular system. Brain-machine interfaces (BMIs) are especially of interest as they do not require any movement or muscular activity; however, their use in clinical practice is limited due to their low accuracy and reliability. Myoelectric systems provide more reliable control, but they can be unfeasible for people with severe disability. Following recent attempts to overcome these limitations, hybrid human-machine interface (h-HMI) technologies have been proposed to provide a more robust input to robotic devices and to extend their use to a wider population of patients. This call seeks original manuscripts describing new research in the field of h-HMIs for the control of rehabilitation or assistive devices. Papers should include at least one (neuro)physiological interface in their hybrid approach. All categories of medical devices—robotic (e.g., end-effector robots, exoskeletons) or non-robotic (e.g., electrical stimulations)—are welcome. Methodological papers, reviews, and theoretical contributions are also welcome.

Dr. Luca Tonin
Dr. Stefano Tortora
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 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

  • hybrid human-machine interface
  • brain-machine interface
  • electroencephalography
  • electromyography
  • electro-oculography
  • rehabilitation robotics
  • assistive robotics
  • neurofeedback
  • functional electrical stimulation
  • multimodal classification

Published Papers (1 paper)

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Research

14 pages, 5756 KiB  
Article
Development of Power-Assist Device for a Manual Wheelchair Using Cycloidal Reducer
by Dae-Jin Jang, Yong-Cheol Kim, Eung-Pyo Hong and Gyoo-Suk Kim
Appl. Sci. 2023, 13(2), 954; https://doi.org/10.3390/app13020954 - 10 Jan 2023
Viewed by 1740
Abstract
This paper presents the design process and driving performance test results of a power-assist module to which a cycloidal reducer is applied in order to convert a manual wheelchair into an electric wheelchair. The types of electrification modules currently used to electrify manual [...] Read more.
This paper presents the design process and driving performance test results of a power-assist module to which a cycloidal reducer is applied in order to convert a manual wheelchair into an electric wheelchair. The types of electrification modules currently used to electrify manual wheelchairs include front-mounted, rear-mounted, and powered wheels. These assist devices are either difficult to carry and transport independently or require excellent hand dexterity to operate. To overcome this problem, a cycloidal reducer with no pin roller, and a novel cycloidal curve were designed to develop a small and easy-to-handle power-assist module that was tested by installing this reducer to a manual wheelchair. As a result of the test, the maximum speed of the wheelchair was 6 km/h, the maximum slope that this wheelchair can climb is 20%, and 0.358 Ah was consumed while the wheelchair moved 360 m in the current consumption test. This showed that it is possible to develop a small-sized power-assist module. In addition, the user can easily electrify the manual wheelchair by adding a small weight without replacing the manual wheel. The power-assist module consists of a DC servo motor, cycloidal reducer, battery, and joystick. Full article
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