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Sensing Technologies in Medical Robot
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Sensing Technologies in Medical Robot

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

Deadline for manuscript submissions: 30 July 2024 | Viewed by 3291

Special Issue Editor

Prof. Dr. Yanding Qin

E-Mail Website
Guest Editor
College of Artificial Intelligence, Nankai University, Tianjin 300350, China
Interests: flexure-based mechanism; micro/nanomanipulation; hysteresis modeling and compensation; laser-based measurement; mechanical dynamics; three-dimensional bioprinting; super-resolution microscopy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Medical robotics, integrating the advantages of the technological strengths of robotics and information sciences, have become the promising technique in surgeries and rehabilitation applications.

In recent years, there has been a strong interest in the development and application of sensing technologies for medical robots, which offer new opportunities for non-invasive diagnosis, monitoring, and treatment in healthcare. With advances in hardware systems and sensing technology, medical robots have become a powerful tool for surgeons to detect and treat human diseases.

This Special Issue aims to discuss the latest advances, applications, and challenges in the field of sensing technologies for medical robots. Topics of interest for this Special Issue include, but are not limited to:

  • Surgical robot;
  • Wearable robot;
  • Rehabilitation robot;
  • Magnetic drive Robot;
  • Human–robot interaction
  • Haptic sensing and feedback;
  • Robot sensor and vision;
  • Intelligent sensing;
  • Emerging sensor technology;
  • Sensor fusion.

Prof. Dr. Yanding Qin
Guest Editor

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

  • medical robot
  • optical navigation
  • magnetic positioning
  • ultrasonic positioning
  • tactile sensing
  • biomedical sensors

Published Papers (3 papers)

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Research

17 pages, 2893 KiB  
Article
DE-AFO: A Robotic Ankle Foot Orthosis for Children with Cerebral Palsy Powered by Dielectric Elastomer Artificial Muscle
by Vahid Mohammadi, Mohammad Tajdani, Mobina Masaei, Sahel Mohammadi Ghalehney, Samuel C. K. Lee and Ahad Behboodi
Sensors 2024, 24(12), 3787; https://doi.org/10.3390/s24123787 - 11 Jun 2024
Viewed by 905
Abstract
Conventional passive ankle foot orthoses (AFOs) have not seen substantial advances or functional improvements for decades, failing to meet the demands of many stakeholders, especially the pediatric population with neurological disorders. Our objective is to develop the first comfortable and unobtrusive powered AFO [...] Read more.
Conventional passive ankle foot orthoses (AFOs) have not seen substantial advances or functional improvements for decades, failing to meet the demands of many stakeholders, especially the pediatric population with neurological disorders. Our objective is to develop the first comfortable and unobtrusive powered AFO for children with cerebral palsy (CP), the DE-AFO. CP is the most diagnosed neuromotor disorder in the pediatric population. The standard of care for ankle control dysfunction associated with CP, however, is an unmechanized, bulky, and uncomfortable L-shaped conventional AFO. These passive orthoses constrain the ankle’s motion and often cause muscle disuse atrophy, skin damage, and adverse neural adaptations. While powered orthoses could enhance natural ankle motion, their reliance on bulky, noisy, and rigid actuators like DC motors limits their acceptability. Our innovation, the DE-AFO, emerged from insights gathered during customer discovery interviews with 185 stakeholders within the AFO ecosystem as part of the NSF I-Corps program. The DE-AFO is a biomimetic robot that employs artificial muscles made from an electro-active polymer called dielectric elastomers (DEs) to assist ankle movements in the sagittal planes. It incorporates a gait phase detection controller to synchronize the artificial muscles with natural gait cycles, mimicking the function of natural ankle muscles. This device is the first of its kind to utilize lightweight, compact, soft, and silent artificial muscles that contract longitudinally, addressing traditional actuated AFOs’ limitations by enhancing the orthosis’s natural feel, comfort, and acceptability. In this paper, we outline our design approach and describe the three main components of the DE-AFO: the artificial muscle technology, the finite state machine (the gait phase detection system), and its mechanical structure. To verify the feasibility of our design, we theoretically calculated if DE-AFO can provide the necessary ankle moment assistance for children with CP—aligning with moments observed in typically developing children. To this end, we calculated the ankle moment deficit in a child with CP when compared with the normative moment of seven typically developing children. Our results demonstrated that the DE-AFO can provide meaningful ankle moment assistance, providing up to 69% and 100% of the required assistive force during the pre-swing phase and swing period of gait, respectively. Full article
(This article belongs to the Special Issue Sensing Technologies in Medical Robot)
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18 pages, 7901 KiB  
Article
A Tension Sensor Array for Cable-Driven Surgical Robots
by Zhangxi Zhou, Jianlin Yang, Mark Runciman, James Avery, Zhijun Sun and George Mylonas
Sensors 2024, 24(10), 3156; https://doi.org/10.3390/s24103156 - 16 May 2024
Viewed by 697
Abstract
Tendon–sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor [...] Read more.
Tendon–sheath structures are commonly utilized to drive surgical robots due to their compact size, flexibility, and straightforward controllability. However, long-distance cable tension estimation poses a significant challenge due to its frictional characteristics affected by complicated factors. This paper proposes a miniature tension sensor array for an endoscopic cable-driven parallel robot, aiming to integrate sensors into the distal end of long and flexible surgical instruments to sense cable tension and alleviate friction between the tendon and sheath. The sensor array, mounted at the distal end of the robot, boasts the advantages of a small size (16 mm outer diameter) and reduced frictional impact. A force compensation strategy was presented and verified on a platform with a single cable and subsequently implemented on the robot. The robot demonstrated good performance in a series of palpation tests, exhibiting a 0.173 N average error in force estimation and a 0.213 N root-mean-square error. In blind tests, all ten participants were able to differentiate between silicone pads with varying hardness through force feedback provided by a haptic device. Full article
(This article belongs to the Special Issue Sensing Technologies in Medical Robot)
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16 pages, 2229 KiB  
Article
Full-Perception Robotic Surgery Environment with Anti-Occlusion Global–Local Joint Positioning
by Hongpeng Wang, Tianzuo Liu, Jianren Chen, Chongshan Fan, Yanding Qin and Jianda Han
Sensors 2023, 23(20), 8637; https://doi.org/10.3390/s23208637 - 22 Oct 2023
Cited by 1 | Viewed by 1243
Abstract
The robotic surgery environment represents a typical scenario of human–robot cooperation. In such a scenario, individuals, robots, and medical devices move relative to each other, leading to unforeseen mutual occlusion. Traditional methods use binocular OTS to focus on the local surgical site, without [...] Read more.
The robotic surgery environment represents a typical scenario of human–robot cooperation. In such a scenario, individuals, robots, and medical devices move relative to each other, leading to unforeseen mutual occlusion. Traditional methods use binocular OTS to focus on the local surgical site, without considering the integrity of the scene, and the work space is also restricted. To address this challenge, we propose the concept of a fully perception robotic surgery environment and build a global–local joint positioning framework. Furthermore, based on data characteristics, an improved Kalman filter method is proposed to improve positioning accuracy. Finally, drawing from the view margin model, we design a method to evaluate positioning accuracy in a dynamic occlusion environment. The experimental results demonstrate that our method yields better positioning results than classical filtering methods. Full article
(This article belongs to the Special Issue Sensing Technologies in Medical Robot)
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