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Machines
Special Issues
Advances in Assistive Robotics
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Advances in Assistive Robotics

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".

Deadline for manuscript submissions: 15 January 2025 | Viewed by 748

Special Issue Editor

Dr. Alejandro Ramirez

E-Mail Website
Guest Editor
Applied Computing Department, Universidade do Vale do Itajai, Itajai, Brazil
Interests: assistive technolgy; robotics

Special Issue Information

Dear Colleagues,

Assistive Robotics is a branch of robotics that aims to assist individuals who have lost certain abilities that are common to the majority of the population. Assistive robots possess enormous potential regarding their ability to enhance individuals’ quality of life. Recent advances in artificial intelligence (AI) and robotics will likely fuel global revenue growth in this domain.

This Special Issue of Machines focuses on the latest scientific and technical research related to these topics in both academic and industrial sectors. Therefore, we welcome the contribution of papers that attend to topics including, but not limited to, the following:

  • assisitive robotics;
  • social robots;
  • wearable robots;
  • rehabilitation robots;
  • assistive technology;
  • human–machine interaction;
  • robotic manipulator;
  • autonomous robot companions.

We are looking forward to receiving your submissions.

Dr. Alejandro Ramirez
Guest Editor

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. Machines 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 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.

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

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Research

63 pages, 37102 KiB  
Article
BLUE SABINO: Development of a BiLateral Upper-Limb Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output
by Christopher K. Bitikofer, Sebastian Rueda Parra, Rene Maura, Eric T. Wolbrecht and Joel C. Perry
Machines 2024, 12(9), 617; https://doi.org/10.3390/machines12090617 - 3 Sep 2024
Viewed by 393
Abstract
Arm and hand function play a critical role in the successful completion of everyday tasks. Lost function due to neurological impairment impacts millions of lives worldwide. Despite improvements in the ability to assess and rehabilitate arm deficits, knowledge about underlying sources of impairment [...] Read more.
Arm and hand function play a critical role in the successful completion of everyday tasks. Lost function due to neurological impairment impacts millions of lives worldwide. Despite improvements in the ability to assess and rehabilitate arm deficits, knowledge about underlying sources of impairment and related sequela remains limited. The comprehensive assessment of function requires the measurement of both biomechanics and neuromuscular contributors to performance during the completion of tasks that often use multiple joints and span three-dimensional workspaces. To our knowledge, the complexity of movement and diversity of measures required are beyond the capabilities of existing assessment systems. To bridge current gaps in assessment capability, a new exoskeleton instrument is developed with comprehensive bilateral assessment in mind. The development of the BiLateral Upper-limb Exoskeleton for Simultaneous Assessment of Biomechanical and Neuromuscular Output (BLUE SABINO) expands on prior iterations toward full-arm assessment during reach-and-grasp tasks through the development of a dual-arm and dual-hand system, with 9 active degrees of freedom per arm and 12 degrees of freedom (six active, six passive) per hand. Joints are powered by electric motors driven by a real-time control system with input from force and force/torque sensors located at all attachment points between the user and exoskeleton. Biosignals from electromyography and electroencephalography can be simultaneously measured to provide insight into neurological performance during unimanual or bimanual tasks involving arm reach and grasp. Design trade-offs achieve near-human performance in exoskeleton speed and strength, with positional measurement at the wrist having an error of less than 2 mm and supporting a range of motion approximately equivalent to the 50th-percentile human. The system adjustability in seat height, shoulder width, arm length, and orthosis width accommodate subjects from approximately the 5th-percentile female to the 95th-percentile male. Integration between precision actuation, human–robot-interaction force-torque sensing, and biosignal acquisition systems successfully provide the simultaneous measurement of human movement and neurological function. The bilateral design enables use with left- or right-side impairments as well as intra-subject performance comparisons. With the resulting instrument, the authors plan to investigate underlying neural and physiological correlates of arm function, impairment, learning, and recovery. Full article
(This article belongs to the Special Issue Advances in Assistive Robotics)
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