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Recent Advances in Medical Robots: Design and Applications

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

Deadline for manuscript submissions: 25 January 2026 | Viewed by 1041

Special Issue Editor


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Guest Editor
Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
Interests: medical engineering; mechanical engineering; robotics; computer vision; AI

Special Issue Information

Dear Colleagues,

The robotization of surgeries and treatments has witnessed remarkable development. Nowadays, with the deepening of the integration of medicine and engineering in this field, an increasing number of surgical and treatment scenarios present new impetus and challenges for medical robots. The development of medical robots is facing new challenges, especially in terms of sensor technology. Advanced medical sensors, including force/torque sensors, optical sensors, and bio-sensors, serve as the nervous system of medical robots, enabling precise perception and real-time feedback during complex surgical procedures. These sensing capabilities are fundamental to achieving safe and effective human–robot collaboration.

In the face of more specialized and diversified surgical needs, more diverse perception methods and decision-making abilities are required. Currently, medical robots are making rapid progress in this field by leveraging cutting-edge sensor technologies such as haptic feedback systems, 3D vision sensors, and miniature in-body sensors. These innovations allow medical robots to not only be executors assisting physicians and therapists in treatment but also extensions of their eyes, hands, and even minds through enhanced sensory capabilities. The integration of multimodal sensor systems has made medical robots indispensable and crucial partners in the future intelligent medical system.

This Special Issue aims to explore more diversified perception and decision-making processes in medical robots, with particular emphasis on novel sensor technologies and their clinical applications. We will showcase the latest progress in medical robot design, including breakthroughs in sensor fusion algorithms, AI-enhanced sensory processing, and miniaturized implantable sensors. Articles focusing on intelligent perception based on artificial intelligence technology, data-driven intelligent control of robots, and efforts to optimize the design process of medical robots will also be included in this Special Issue. We expect that engineering applications can participate in the treatment process more efficiently, intelligently, and safely, thus bringing a higher quality of life to more people, not just patients.

Dr. Zhenguo Nie
Guest Editor

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Keywords

  • medical robot
  • multimodal sensing
  • intelligent sensing
  • haptic perception
  • human–robot interaction
  • control
  • teleoperation
  • robot design

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Published Papers (1 paper)

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Research

17 pages, 3323 KB  
Article
Enhancing Torque Output for a Magnetic Actuation System for Robotic Spinal Distraction
by Yumei Li, Zikang Li, Ding Lu, Tairan Peng, Yunzhi Chen, Gang Fu, Zhenguo Nie and Fangyuan Wei
Sensors 2025, 25(20), 6497; https://doi.org/10.3390/s25206497 - 21 Oct 2025
Viewed by 645
Abstract
Magnetically controlled spinal growing rods, used for treating early-onset scoliosis (EOS), face a critical clinical limitation: insufficient distraction force. Compounding this issue is the inherent inability to directly monitor the mechanical output of such implants in vivo, which challenges their safety and efficacy. [...] Read more.
Magnetically controlled spinal growing rods, used for treating early-onset scoliosis (EOS), face a critical clinical limitation: insufficient distraction force. Compounding this issue is the inherent inability to directly monitor the mechanical output of such implants in vivo, which challenges their safety and efficacy. To overcome these limitations, optimizing the rotor’s maximum torque is essential. Furthermore, defining the “continuous rotation domain” establishes a vital safety boundary for stable operation, preventing loss of synchronization and loss of control, thus safeguarding the efficacy of future clinical control strategies. In this study, a transient finite element magnetic field simulation model of a circumferentially distributed permanent magnet–rotor system was established using ANSYS Maxwell (2024). The effects of the clamp angle between the driving magnets and the rotor, the number of pole pairs, the rotor’s outer diameter, and the rotational speed of the driving magnets on the rotor’s maximum torque were systematically analyzed, and the optimized continuous rotation domain of the rotor was determined. The results indicated that when the clamp angle was set at 120°, the number of pole pairs was one, the rotor outer diameter was 8 mm, the rotor achieved its maximum torque and exhibited the largest continuous rotation domain, while the rotational speed of the driving magnets had no effect on maximum torque. Following optimization, the maximum torque of the simulation increased by 201% compared with the pre-optimization condition, and the continuous rotation domain was significantly enlarged. To validate the simulation, a rotor torque measurement setup incorporating a torque sensor was constructed. Experimental results showed that the maximum torque improved from 30 N·mm before optimization to 90 N·mm after optimization, while the driving magnets maintained stable rotation throughout the process. Furthermore, a spinal growing rod test platform equipped with a pressure sensor was developed to evaluate actuator performance and measure the maximum distraction force. The optimized growing rod achieved a peak distraction force of 413 N, nearly double that of the commercial MAGEC system, which reached only 208 N. The simulation and experimental methodologies established in this study not only optimizes the device’s performance but also provides a viable pathway for in vivo performance prediction and monitoring, addressing a critical need in smart implantable technology. Full article
(This article belongs to the Special Issue Recent Advances in Medical Robots: Design and Applications)
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