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Advances in Robotics and Sensors for Rehabilitation

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensors and Robotics".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 1446

Special Issue Editors


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Guest Editor
Department of Automation, Kaunas University of Technology, 51367 Kaunas, Lithuania
Interests: robotics; AI; computer vision
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Electrical and Electronics Engineering Faculty, Kaunas University of Technology, 51367 Kaunas, Lithuania
Interests: AI; computer vision; electrical drives

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Guest Editor Assistant
Department of Rehabilitation, Kauno Kolegija Higher Education Institution, Medicine Faculty, Kaunas, Lithuania
Interests: rehabilitation; health promotion; cognitive aging; exercise physiology Social media account

Special Issue Information

Dear Colleagues,

The field of rehabilitation is undergoing transformation driven by the convergence of robotics and sensor technologies. This Special Issue of Sensors, entitled “Advances in Robotics and Sensors for Rehabilitation”, explores this exciting intersection, showcasing cutting-edge research that is transforming how we recover from injury and illness.

Regaining mobility and independence is a core goal of rehabilitation. This Special Issue highlights the development of robotic assistive devices, such as exoskeletons and robotic wheelchairs, that physically aid patients in movement therapy. It delves into the critical role of sensors in these devices, providing real-time feedback on a patient’s progress and enabling personalized therapy plans.

Beyond physical assistance, this Special Issue explores the growing prominence of wearable sensors. These unobtrusive devices continuously monitor vital signs, movement patterns, and even environmental factors, allowing for remote patient monitoring and the prevention of secondary complications. The integration of artificial intelligence with sensor data further enhances rehabilitation by creating intelligent systems that adapt to individual needs and provide real-time feedback.

This Special Issue welcomes contributions that showcase the latest advancements in robotics, sensor technology, and the application of artificial intelligence methods for rehabilitation. We invite researchers to share their work on the following topics:

  • Novel robotic assistive devices for physical therapy;
  • Sensor integration for real-time patient monitoring;
  • Wearable technology for at-home rehabilitation;
  • Human–robot interaction in rehabilitation settings;
  • The application of artificial intelligence and machine learning for personalized therapy.

This Special Issue aims to accelerate the development of innovative solutions that empower individuals on their path to recovery by collaboration between robotics, sensors, and AI experts.

Dr. Vidas Raudonis
Dr. Arunas Lipnickas
Guest Editors

Dr. Ligita Šilinė
Guest Editor Assistant

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. Sensors 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 2600 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

  • robotic assistive devices
  • sensor integration
  • wearable technology
  • remote patient monitoring

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Published Papers (1 paper)

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Research

12 pages, 1186 KiB  
Article
Cardiac Function and Fatigue During Exoskeleton-Assisted Sit-to-Stand Maneuver and Walking in People with Stroke with Moderate to Severe Gait Disability: A Pilot Cross-Sectional Study
by Raimondas Kubilius, Darius Ruočkus, Vitalija Stonkuvienė, Rugilė Vareikaitė, Rebecca Cardini and Thomas Bowman
Sensors 2025, 25(1), 172; https://doi.org/10.3390/s25010172 - 31 Dec 2024
Viewed by 935
Abstract
Background. Wearable powered exoskeletons could be used to provide robotic-assisted gait training (RAGT) in people with stroke (PwST) and walking disability. The study aims to compare the differences in cardiac function, fatigue, and workload during activities of daily living (ADLs), while wearing an [...] Read more.
Background. Wearable powered exoskeletons could be used to provide robotic-assisted gait training (RAGT) in people with stroke (PwST) and walking disability. The study aims to compare the differences in cardiac function, fatigue, and workload during activities of daily living (ADLs), while wearing an exoskeleton. Methods. Five PwST were recruited in this pilot cross-sectional study. We observed three experimental conditions: walking without and with the UAN.GO exoskeleton and walking with the UAN.GO combined with the OPTIGO walker. Each condition included five trials related to ADLs such as sitting and walking. Results. No statistically significant difference was found between heart rate and R–R of ECG data while comparing all the observed conditions during each respective trial. The NASA Task Load Index did not show significant differences across all trials, except for a significant difference between Condition 2 and Condition 3 in Trial 4 (p = 0.043). However, walking and sit-to-stand tasks seem to be more challenging according to the NASA-TLX. Only one participant scored over 70 points on the System Usability Scale. The TSQ-WT scores for conditions 2 and 3 were 62 (56.5–72.5) and 70 (66.5–75) points, respectively. Conclusions. This study suggests that UAN.GO exoskeleton could be used for RAGT in PwST with disability without compromising cardiovascular function. Full article
(This article belongs to the Special Issue Advances in Robotics and Sensors for Rehabilitation)
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