Intelligent Systems, Robots and Devices for Healthcare and Rehabilitation

Dear Colleagues,

Over time, the motor skills of older adults and people with neuromuscular disorders gradually decline, affecting both movement speed and accuracy. Intelligent healthcare and biomedical systems have had a major impact on this field over the past decade and are expected to revolutionize rehabilitation and the treatment of movement disorders caused by aging, stroke, and neuromuscular diseases. How to assess and support motor improvement in this field is crucial.

This requires more quantitative methods based on the collection and processing of biological signals as well as control actuators to assist and resist for rehabilitation and healthcare systems.

Relevant are advances in neural signal acquisition, machine learning processes of neural signals, and computer as well as robotic technologies for assisting humans. These areas have the potential to support rehabilitation and healthcare strategies by providing standards for biomedical engineering.

We invite researchers to submit original research papers and review articles that address novel methods for rehabilitation that promote advances to help patients and older adults with motor impairments, including brain–machine interfaces, prosthetics, rehabilitation robots, and control actuators. These new methods promote the advancement of intelligent healthcare and biomedical systems.

Potential topics include, but are not limited to, the following:

• Actuator control methods for interactions between human and devices.
• Novel rehabilitation/healthcare systems.
• Assistive technologies for patients with motor control impairments.
• Personalized rehabilitation interfaces for adapted physical activity.
• New techniques using deep learning and machine learning.
• Internet of Medical Things (IoMT).
• Biomimetic robots and home support robots.

Dr. Duk Shin
Dr. JaeHyo Kim
Dr. Abdelkader Nasreddine Belkacem
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at mdpi.longhoe.net 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. Actuators 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.

• intelligent healthcare and biomedical systems
• rehabilitation
• actuator control
• biomimetic robots

Title: Evaluation of the motor control impairments of older adults with mild cognitive impairment using virtual reality environment
Authors: Hyeonseok Kim1, Yeongdae Kim2, Gyuseok Shim3, Mayumi Tokuda4, Jongho Lee4,5*, and Jaehyo Kim3*
Affiliation: 1 Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA 92093, United States 2 Department of Computer Science, University of Colorado Denver, Aurora, CO, United States 3 Department of Mechanical and Control Engineering, Handong Global University, Pohang 37554, Korea 4 Division of Health Sciences, Graduate School of Sustainable Systems Science, Komatsu University, Komatsu 923-0961, Japan 5 Department of Clinical Engineering, Komatsu University, Komatsu 923-0961, Japan
Abstract: In this study, we examined motor control impairments of older adults with mild cognitive impairment (MCI) using virtual reality environment. In particular, we aimed to investigate mainly the functions loss to feedforward/feedback (visual and proprioceptive feedback) affected by aging-induced MCI during reaching. We compared healthy older adults to adults with MCI who were instructed to perform a reaching task in an immersive virtual reality environment under two conditions: (1) using a visible cursor and (2) using an invisible cursor. Our results revealed that errors at the peak speed under visible and invisible conditions were not significantly different between the healthy and MCI groups. However, for the MCI group, the difference in errors between the visible and invisible conditions was significant. When the movement time was observed, the difference was distinctive, showing that the MCI group’s time exponentially increased depending on the displacement, whereas the healthy group’s time was consistent over the entire displacement range. In conclusion, our study confirmed that proprioception is a specifically important factor for the motor control impairments degenerated by MCI.