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Rehabilitation Robot with Intelligent Sensing System

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 950

Special Issue Editors

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
Interests: rehabilitation medicine; rehabilitation engineering; hand rehabilitation robots
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
Interests: rehabilitation engineering; medical flexible sensing; simulation design of optical; mechanical and electrical integration; mechanical engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Considering the development of rehabilitation engineering, rehabilitation robots, especially upper limb rehabilitation robots, lower limb rehabilitation robots and hand rehabilitation robot systems, show great application potential. An important symbol of a high-end rehabilitation robot is human–machine integration technology that uses high-end sensors to realize intention recognition. Accurate recognition of motor intention is of great scientific significance and clinical value for accurate rehabilitation based on real motor intention. Sensing sensors and algorithms are important problems that restrict the application of rehabilitation robots. The application of flexible sensing systems and intelligent algorithms has become one solution to this problem. This Special Issue aims to collect high-quality original research focused on the development of rehabilitation robots and methods for intelligent sensing, modeling, learning and control of robots.

  • Modeling and development of rehabilitation robot;
  • Design of wearable device controlled by upper limb rehabilitation robot;
  • Modeling, development and experiment of hand rehabilitation robot;
  • Lower limb rehabilitation robot and its application;
  • Research and control of prosthetics;
  • Wearable device based on intelligent flexible sensing;
  • Information fusion technology of multimode sensing;
  • Human robot cooperative learning and control.

Dr. Kai Guo
Prof. Hongbo Yang
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

  • rehabilitation robot
  • wearable robot
  • intelligent system

Published Papers (1 paper)

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Research

13 pages, 3970 KiB  
Article
Motion-Based Control Strategy of Knee Actuated Exoskeletal Gait Orthosis for Hemiplegic Patients: A Feasibility Study
by Yoon Heo, Hyuk-Jae Choi, Jong-Won Lee, Hyeon-Seok Cho and Gyoo-Suk Kim
Appl. Sci. 2024, 14(1), 301; https://doi.org/10.3390/app14010301 - 29 Dec 2023
Cited by 1 | Viewed by 718
Abstract
In this study, we developed a unilateral knee actuated exoskeletal gait orthosis (KAEGO) for hemiplegic patients to conduct gait training in real-world environments without spatial limitations. For this purpose, it is crucial that the controller interacts with the patient’s gait intentions. This study [...] Read more.
In this study, we developed a unilateral knee actuated exoskeletal gait orthosis (KAEGO) for hemiplegic patients to conduct gait training in real-world environments without spatial limitations. For this purpose, it is crucial that the controller interacts with the patient’s gait intentions. This study newly proposes a simple gait control strategy that detects the gait state and recognizes the patient’s gait intentions using only the motion information of the lower limbs obtained from an embedded inertial measurement units (IMU) sensor and a knee angle sensor without employing ground reaction force (GRF) sensors. In addition, a torque generation method based on negative damping was newly applied as a method to determine the appropriate amount of assistive torque to support flexion or extension movements of the knee joint. To validate the performance of the developed KAEGO and the effectiveness of our proposed gait control strategy, we conducted walking tests with a hemiplegic patient. These tests included verifying the accuracy of gait recognition and comparing the metabolic cost of transport (COT). The experimental results confirmed that our gait control approach effectively recognizes the patient’s gait intentions without GRF sensors and reduces the metabolic cost by approximately 8% compared to not wearing the device. Full article
(This article belongs to the Special Issue Rehabilitation Robot with Intelligent Sensing System)
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