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Advanced Technologies in Medical and Surgical Robotics
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Advanced Technologies in Medical and Surgical Robotics

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 21426

Special Issue Editors

Dr. Bai Chen

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: surgical robotics; continuum robot; cable driven robot
Dr. Feng Ju

E-Mail Website
Guest Editor
College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Interests: surgical robotics; continuum robot; tactile sensing; haptics; piezoelectric sensors and actuators
Dr. Bo Lu

E-Mail Website
Guest Editor
School of Mechanical and Electrical Engineering, Soochow University, Suzhou 215131, China
Interests: surgical robotics; computer vision; robot learning; surgical navigation; skill learning; task automation
Dr. Fuxin Du

E-Mail Website
Guest Editor
School of Mechanical Engineering, Shandong University, Jinan 250061, China
Interests: medical robotics; continuum robot, machine tools, motion control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Surgical robotics is the most cutting-edge medical technology of modern times. It offers many benefits to patients, including shorter hospitalization times, reduced pain, faster recovery, smaller incisions, etc. Surgical robots drive clinical technology innovation in many aspects, from preoperative planning to intraoperative execution to postoperative rehabilitation. At present, the advent of the smart medical era is introducing new technologies, such as soft/flexible robotics, intelligent sensing and control, haptics, artificial intelligence, and AR/VR, into the field. Nevertheless, it may bring some technical challenges for the deep integration of medical and robotics technologies.

This Special Issue aims to invite and collate high-quality original research and review articles on the latest advances in the theory, methods, and applications of medical and surgical robotics. Potential topics include, but are not limited to, the following:

  • Medical/surgical robot systems.
  • Soft/continuum robots.
  • Sensing technologies for surgical robots.
  • Control technologies for surgical robots.
  • Haptics for surgical robots.
  • AR/VR for surgical robots.
  • Autonomous robotic surgery technologies.
  • Computer vision and artificial intelligence for surgical robots.
  • Preoperative planning for robotic surgery.
  • Intraoperative tracking and navigation.
  • Applications of surgical robots.

Dr. Bai Chen
Dr. Feng Ju
Dr. Bo Lu
Dr. Fuxin Du
Guest Editors

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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

  • surgical robot
  • medical robot
  • soft robot
  • continuum robot
  • shape and position sensing
  • tactile and force sensing
  • haptics
  • autonomous robotic surgery
  • localization and navigation

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Published Papers (6 papers)

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Research

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19 pages, 8138 KiB  
Article
Dynamic Virtual Fixture Generation Based on Intra-Operative 3D Image Feedback in Robot-Assisted Minimally Invasive Thoracic Surgery
by Yunze Shi, Peizhang Zhu, Tengyue Wang, Haonan Mai, Xiyang Yeh, Liangjing Yang and Jingfan Wang
Sensors 2024, 24(2), 492; https://doi.org/10.3390/s24020492 - 12 Jan 2024
Viewed by 1395
Abstract
This paper proposes a method for generating dynamic virtual fixtures with real-time 3D image feedback to facilitate human–robot collaboration in medical robotics. Seamless shared control in a dynamic environment, like that of a surgical field, remains challenging despite extensive research on collaborative control [...] Read more.
This paper proposes a method for generating dynamic virtual fixtures with real-time 3D image feedback to facilitate human–robot collaboration in medical robotics. Seamless shared control in a dynamic environment, like that of a surgical field, remains challenging despite extensive research on collaborative control and planning. To address this problem, our method dynamically creates virtual fixtures to guide the manipulation of a trocar-placing robot arm using the force field generated by point cloud data from an RGB-D camera. Additionally, the “view scope” concept selectively determines the region for computational points, thereby reducing computational load. In a phantom experiment for robot-assisted port incision in minimally invasive thoracic surgery, our method demonstrates substantially improved accuracy for port placement, reducing error and completion time by 50% (p=1.06×10−2) and 35% (p=3.23×10−2), respectively. These results suggest that our proposed approach is promising in improving surgical human–robot collaboration. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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21 pages, 13993 KiB  
Article
Coupling Analysis of Compound Continuum Robots for Surgery: Another Line of Thought
by Hangxing Wei, Gang Zhang, Shengsong Wang, Peng Zhang, Jing Su and Fuxin Du
Sensors 2023, 23(14), 6407; https://doi.org/10.3390/s23146407 - 14 Jul 2023
Cited by 5 | Viewed by 1830
Abstract
The compound continuum robot employs both concentric tube components and cable-driven continuum components to achieve its complex motions. Nevertheless, the interaction between these components causes coupling, which inevitably leads to reduced accuracy. Consequently, researchers have been striving to mitigate and compensate for this [...] Read more.
The compound continuum robot employs both concentric tube components and cable-driven continuum components to achieve its complex motions. Nevertheless, the interaction between these components causes coupling, which inevitably leads to reduced accuracy. Consequently, researchers have been striving to mitigate and compensate for this coupling-induced error in order to enhance the overall performance of the robot. This paper leverages the coupling between the components of the compound continuum robot to accomplish specific surgical procedures. Specifically, the internal concentric tube component is utilized to induce motion in the cable-driven external component, which generates coupled motion under the constraints of the cable. This approach enables the realization of high-precision surgical operations. Specifically, a kinematic model for the proposed robot is established, and an inverse kinematic algorithm is developed. In this inverse kinematic algorithm, the solution of a highly nonlinear system of equations is simplified into the solution of a single nonlinear equation. To demonstrate the effectiveness of the proposed approach, simulations are conducted to evaluate the efficiency of the algorithm. The simulations conducted in this study indicate that the proposed inverse kinematic (IK) algorithm improves computational speed by a significant margin. Specifically, it achieves a speedup of 2.8 × 103 over the Levenberg–Marquardt (LM) method. In addition, experimental results demonstrate that the coupled-motion system achieves high levels of accuracy. Specifically, the repetitive positioning accuracy is measured to be 0.9 mm, and the tracking accuracy is 1.5 mm. This paper is significant for dealing with the coupling of the compound continuum robot. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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17 pages, 1679 KiB  
Article
Physiological Metrics of Surgical Difficulty and Multi-Task Requirement during Robotic Surgery Skills
by Chiho Lim, Juan Antonio Barragan, Jason Michael Farrow, Juan P. Wachs, Chandru P. Sundaram and Denny Yu
Sensors 2023, 23(9), 4354; https://doi.org/10.3390/s23094354 - 28 Apr 2023
Cited by 5 | Viewed by 1748
Abstract
Previous studies in robotic-assisted surgery (RAS) have studied cognitive workload by modulating surgical task difficulty, and many of these studies have relied on self-reported workload measurements. However, contributors to and their effects on cognitive workload are complex and may not be sufficiently summarized [...] Read more.
Previous studies in robotic-assisted surgery (RAS) have studied cognitive workload by modulating surgical task difficulty, and many of these studies have relied on self-reported workload measurements. However, contributors to and their effects on cognitive workload are complex and may not be sufficiently summarized by changes in task difficulty alone. This study aims to understand how multi-task requirement contributes to the prediction of cognitive load in RAS under different task difficulties. Multimodal physiological signals (EEG, eye-tracking, HRV) were collected as university students performed simulated RAS tasks consisting of two types of surgical task difficulty under three different multi-task requirement levels. EEG spectral analysis was sensitive enough to distinguish the degree of cognitive workload under both surgical conditions (surgical task difficulty/multi-task requirement). In addition, eye-tracking measurements showed differences under both conditions, but significant differences of HRV were observed in only multi-task requirement conditions. Multimodal-based neural network models have achieved up to 79% accuracy for both surgical conditions. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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15 pages, 1280 KiB  
Article
Path Planning for Obstacle Avoidance of Robot Arm Based on Improved Potential Field Method
by Xinkai Xia, Tao Li, Shengbo Sang, Yongqiang Cheng, Huanzhou Ma, Qiang Zhang and Kun Yang
Sensors 2023, 23(7), 3754; https://doi.org/10.3390/s23073754 - 5 Apr 2023
Cited by 16 | Viewed by 6352
Abstract
In medical and surgical scenarios, the trajectory planning of a collaborative robot arm is a difficult problem. The artificial potential field (APF) algorithm is a classic method for robot trajectory planning, which has the characteristics of good real-time performance and low computing consumption. [...] Read more.
In medical and surgical scenarios, the trajectory planning of a collaborative robot arm is a difficult problem. The artificial potential field (APF) algorithm is a classic method for robot trajectory planning, which has the characteristics of good real-time performance and low computing consumption. There are many variants of the APF algorithm, among which the most widely used variants is the velocity potential field (VPF) algorithm. However, the traditional VPF algorithm has inherent defects and problems, such as easily falling into local minimum, being unable to reach the target, poor dynamic obstacle avoidance ability, and safety and efficiency problems. Therefore, this work presents the improved velocity potential field (IVPF) algorithm, which considers direction factors, obstacle velocity factor, and tangential velocity. When encountering dynamic obstacles, the IVPF algorithm can avoid obstacles better to ensure the safety of both the human and robot arm. The IVPF algorithm also does not easily fall into a local problem when encountering different obstacles. The experiments informed the RRT* algorithm, VPF algorithm, and IVPF algorithm for comparison. Compared with the informed RRT* and VPF algorithm, the result of experiments indicate that the performances of the IVPF algorithm have significant improvements when dealing with different obstacles. The main aim of this paper is to provide a safe and efficient path planning algorithm for the robot arm in the medical field. The proposed algorithm can ensure the safety of both the human and the robot arm when the medical and surgical robot arm is working, and enables the robot arm to cope with emergencies and perform tasks better. The application of the proposed algorithm could make the collaborative robots work in a flexible and safe condition, which could open up new opportunities for the future development of medical and surgical scenarios. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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14 pages, 3985 KiB  
Article
Modeling of and Experimenting with Concentric Tube Robots: Considering Clearance, Friction and Torsion
by Tianxiang Liu, Gang Zhang, Peng Zhang, Tianyu Cheng, Zijie Luo, Shengsong Wang and Fuxin Du
Sensors 2023, 23(7), 3709; https://doi.org/10.3390/s23073709 - 3 Apr 2023
Cited by 4 | Viewed by 2757
Abstract
Concentric tube robots (CTRs) are a promising prospect for minimally invasive surgery due to their inherent compliance and ability to navigate in constrained environments. Existing mechanics-based kinematic models typically neglect friction, clearance, and torsion between each pair of contacting tubes, leading to large [...] Read more.
Concentric tube robots (CTRs) are a promising prospect for minimally invasive surgery due to their inherent compliance and ability to navigate in constrained environments. Existing mechanics-based kinematic models typically neglect friction, clearance, and torsion between each pair of contacting tubes, leading to large positioning errors in medical applications. In this paper, an improved kinematic modeling method is developed. The effect of clearance on tip position during concentric tube assembly is compensated by the database method. The new kinematic model is mechanic-based, and the impact of friction moment and torsion on tubes is considered. Integrating the infinitesimal torsion of the concentric tube robots eliminates the errors caused by the interaction force between the tubes. A prototype is built, and several experiments with kinematic models are designed. The results indicate that the error of tube rotations is less than 2 mm. The maximum error of the feeding experiment does not exceed 0.4 mm. The error of the new modeling method is lower than that of the previous kinematic model. This paper has substantial implications for the high-precision and real-time control of concentric tube robots. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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Review

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49 pages, 4312 KiB  
Review
Microsurgery Robots: Applications, Design, and Development
by Tiexin Wang, Haoyu Li, Tanhong Pu and Liangjing Yang
Sensors 2023, 23(20), 8503; https://doi.org/10.3390/s23208503 - 16 Oct 2023
Cited by 9 | Viewed by 6343
Abstract
Microsurgical techniques have been widely utilized in various surgical specialties, such as ophthalmology, neurosurgery, and otolaryngology, which require intricate and precise surgical tool manipulation on a small scale. In microsurgery, operations on delicate vessels or tissues require high standards in surgeons’ skills. This [...] Read more.
Microsurgical techniques have been widely utilized in various surgical specialties, such as ophthalmology, neurosurgery, and otolaryngology, which require intricate and precise surgical tool manipulation on a small scale. In microsurgery, operations on delicate vessels or tissues require high standards in surgeons’ skills. This exceptionally high requirement in skills leads to a steep learning curve and lengthy training before the surgeons can perform microsurgical procedures with quality outcomes. The microsurgery robot (MSR), which can improve surgeons’ operation skills through various functions, has received extensive research attention in the past three decades. There have been many review papers summarizing the research on MSR for specific surgical specialties. However, an in-depth review of the relevant technologies used in MSR systems is limited in the literature. This review details the technical challenges in microsurgery, and systematically summarizes the key technologies in MSR with a developmental perspective from the basic structural mechanism design, to the perception and human–machine interaction methods, and further to the ability in achieving a certain level of autonomy. By presenting and comparing the methods and technologies in this cutting-edge research, this paper aims to provide readers with a comprehensive understanding of the current state of MSR research and identify potential directions for future development in MSR. Full article
(This article belongs to the Special Issue Advanced Technologies in Medical and Surgical Robotics)
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