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Embodied Intelligence-Based Robotics in Medicine: Sensor-Driven Innovations for Healthcare

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

Deadline for manuscript submissions: 1 July 2026 | Viewed by 1494

Special Issue Editors


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Guest Editor
Institute of Biomedical Manufacturing, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China
Interests: computer assisted surgery; medical image analysis; surgical navigation; VR/AR/MR technology in medicine; surgical robotics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
College of Computer Science and Technology, University of Huaqiao, Xiamen 361021, China
Interests: medical image computing; computer-aided surgery; medical robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid advancement of technology, embodied intelligence-based robots are profoundly transforming the future of the healthcare industry. Sensor technology, as the core driving force, endows medical robots with more sensitive perception capabilities, enabling them to demonstrate great potential in diagnosis, treatment, and rehabilitation. Sensor-driven medical robots, equipped with precise perception and efficient data processing capabilities, can achieve more accurate surgical operations, more efficient disease monitoring, and more personalized rehabilitation plans, thereby providing strong support for the intelligent development of healthcare.

This Special Issue focuses on innovative technologies of sensor-driven medical robots and their applications in medical practice, aiming to explore how these technologies reshape healthcare service models and address emerging challenges. We hope to accelerate the translation of intelligent robot technology from the laboratory to clinical applications through interdisciplinary communication and cooperation.

In this Special Issue, original research articles and reviews are welcome. Research areas may include, but are not limited to, the following:

  • Sensor-driven medical robots.
  • Embodied intelligence-based medical robots.
  • Real-time data processing and feedback mechanisms.
  • Human–robot interaction in medical settings.
  • Clinical applications of sensor-enhanced robotic systems.
  • Safety analysis and control strategies for medical robots.
  • AI algorithms for medical robots.
  • Robotic-assisted surgical planning.
  • Sensor fusion for medical robots.
  • Immersive teleoperation.
  • Medical image computing.
  • Surgical navigation.
  • Image-guided interventions.
  • VR/AR/MR technologies in medicine.

We look forward to receiving your contributions.

Prof. Dr. Xiaojun Chen
Dr. Jiangchang Xu
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 250 words) can be sent to the Editorial Office for assessment.

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

  • embodied intelligence
  • sensor-driven medical robots
  • advanced sensors
  • human–robot interaction
  • intelligent control
  • sensor fusion
  • medical image computing

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Published Papers (1 paper)

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Research

24 pages, 11596 KB  
Article
Advancing Home Rehabilitation: The PlanAID Robot’s Approach to Upper-Body Exercise Through Impedance Control
by David Breton, Thierry Laliberté, Andréanne K. Blanchette and Alexandre Campeau-Lecours
Sensors 2026, 26(1), 175; https://doi.org/10.3390/s26010175 - 26 Dec 2025
Viewed by 735
Abstract
Rehabilitation robots are a leading solution towards bridging the gap between the growing number of rehabilitation patients requiring therapy and the limited availability of healthcare professionals. However, existing robotic systems are often bulky and expensive, limiting their ability to provide widespread, repetitive, and [...] Read more.
Rehabilitation robots are a leading solution towards bridging the gap between the growing number of rehabilitation patients requiring therapy and the limited availability of healthcare professionals. However, existing robotic systems are often bulky and expensive, limiting their ability to provide widespread, repetitive, and intensive exercises. This paper presents the development of an impedance-based control strategy designed to provide safe and compliant upper-body passive and active exercises on the low-cost PlanAID robot, which is built using consumer-grade components. The system’s functionalities are evaluated using a high-precision force sensor. Results show that the PlanAID exhibits performance comparable to seminal devices such as the MIT-Manus, achieving a similar applicable reaction force target of 28 N and reflected inertia of 1.1 kg. Although the overall performance is comparable, the low-cost PlanAID prototype suffers from reduced coupled stability margins, limiting the maximum achievable virtual spring constant to 1100 N/m. Despite this limitation, the stiffness values required in practical applications remain low, suggesting that the PlanAID could potentially be a viable candidate for real-world rehabilitation. Initial user feedback was obtained through a preliminary qualitative trial involving healthy subjects. Full article
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