Medical Robotics

Elson, Daniel S.; Cleary, Kevin; Dupont, Pierre E.; Merrifield, Robert; Riviere, Cameron N.

doi:10.1007/s10439-018-02127-7

Cited by 8 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At some times, none of these treatments work, so patient-centric customized approaches are taken as treatments. These are usually used in diseases such as Parkinson disease and Alzheimer [31].…”

Section: J Evaluation Of Improvementmentioning

confidence: 99%

See 1 more Smart Citation

Design of Robot Manipulators and Functional Classification of Medical Robots

Swarnalatha¹,

Menon²

2022

International Journal on Advanced Science, Engineering and Information Technology

View full text Add to dashboard Cite

This paper intended to conduct research based on medical robotics, which fundamentally couple information to enhance the performance of human abilities significantly, in this case, surgical interventions, rehabilitation, or simply helping differently-abled people perform daily tasks. This research work aims to comprehend principal concepts in medical robotic designing, analysis, and realtime control of robotic systems within the context of medical applications. Extensive research on telerobotic systems and their applications in robot-assisted minimally invasive surgery/telesurgery is a major aspect of this research. The core aspects focus on the application, functionality, and theoretical aspects of interactive robotic technologies in medicine. Surgical, physiotherapy, and neurorehabilitative robotic systems are significant outlooks of medical robotics. Technological aspects, such as instrumentation, mechanisms, imaging, and simulation, were conducted using MATLAB and Webot software. Simulations using software usage was focused on designing robotic medical models and differentiated using functional classification. Three-dimensional robots with better dexterity and degree of freedom were simulated using Webot software. This research work proposes new approaches of augmented reality aiding medical surgeries whereby three-dimensional visualization of organs is detailed as the future of medical applications. Robotic Kinematics and algorithms are studied in detail when designing these robots on CAD/CAM. Comparative studies based on already implemented medical robots were also conducted. The functionality, drawbacks, ethical issues, and consents of patients are comprehended in detail in this research.

show abstract

Section: J Evaluation Of Improvementmentioning

confidence: 99%

“…This robot can understand every possible emotion communicated by the patient. Socially Assistive Robots (SAR) are therapeutic for many disorders for children, too [31].…”

Section: K Behavioral Therapymentioning

confidence: 99%

Design of Robot Manipulators and Functional Classification of Medical Robots

Swarnalatha¹,

Menon²

2022

International Journal on Advanced Science, Engineering and Information Technology

View full text Add to dashboard Cite

show abstract

“…With the rapid development and application of medical robotics, 7 the path planning for robot‐assisted pelvic fracture closed reduction (RPFCR) has attracted broad researchers. The RPFCR path planning can be divided into two steps: collision detection and path search.…”

Section: Introductionmentioning

confidence: 99%

Autonomous path planning for robot‐assisted pelvic fracture closed reduction with collision avoidance

Pan

Chen

et al. 2022

Robotics Computer Surgery

View full text Add to dashboard Cite

Background: Robot-assisted pelvic fracture closed reduction (RPFCR) positively contributes to patient treatment. However, the current path planning suffers from incomplete obstacle avoidance and long paths. Method:A collision detection method is proposed for applications in the pelvic environment to improve the safety of RPFCR surgery. Meanwhile, a defined orientation planning strategy (OPS) and linear sampling search (LSS) are coupled into the A* algorithm to optimise the reduction path. Subsequently, pelvic in vitro experimental platform is built to verify the augmented A*algorithm's feasibility. Results:The augmented A* algorithm planned the shortest path for the same fracture model, and the paths planned by the A* algorithm and experience-based increased by 56.12% and 89.02%, respectively. Conclusions:The augmented A* algorithm effectively improves surgical safety and shortens the path length, which can be adopted as an effective model for developing RPFCR path planning. K E Y W O R D SA* algorithm, collision detection, path planning, pelvic closed reduction | INTRODUCTIONUnstable pelvic fractures are the most severe injury in the body, accounting for 2%-8% of all fractures and a mortality rate of 6%-31%. 1,2 A safe and precise anatomical reduction is the cornerstone of treating pelvic fractures. 3 As a modern technology with high precision, reliability, and intelligence, robotics is widely used in medical, industrial, and aerospace fields. Therefore, the reduction movements during pelvic fracture closed reduction surgery can be performed by controlling the robot. [4][5][6] With the rapid development and application of medical robotics, 7 the path planning for robot-assisted pelvic fracture closed reduction (RPFCR) has attracted broad researchers. The RPFCR path planning can be divided into two steps: collision detection and path search.The pelvic environment is complex, with many soft and hard tissues. 8 Thus, it is necessary to detect collisions between bones or between bones and soft tissues in preoperative path planning. Meanwhile, a rational and effective path search method is required to cut the surgical intervention time.The main contribution of this paper is to propose a path-planning method for RPFCR, which improves the surgery's safety and the universality of the path planning and reduces the length of the reduction path. Firstly, the fracture model is discretised into computable point cloud data. Based on the point set of the sacrum, the space where the sacrum is located is divided into several small subspaces using the Octree data structure. Then, the point set of the dislocated ilium is traversed to conduct overlap tests with the sacral subspace to detect the collision between objects. Secondly, this paper defined an orientation planning strategy (OPS), which means changing the ilium's orientation with a small step length to avoid high reduction resistance caused by a one-time adjustment. And a linear sampling search (LSS) method is proposed to shorten the reduction path further. Finally, the

show abstract

“…e rapid rise and popularization of robotics technology have made robots no longer limited to manufacturing, but they are also developing towards the field of medical services [1,2]. At present, many foreign rehabilitation medical institutions have used rehabilitation robots to provide rehabilitation training services for patients [3].…”

Section: Introductionmentioning

confidence: 99%

A Novel Human-Machine Collaboration Model of an Ankle Joint Rehabilitation Robot Driven by EEG Signals

Shi

Yang

Zhang

2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

With the emergence of the phenomenon of social aging, the elderly have frequent physical movement disorders. In particular, the movement disorder of the ankle joint seriously affects the daily life of the elderly. Rehabilitation robots are of great significance for improving the efficiency of rehabilitation, ensuring the quality of rehabilitation, and reducing the labor intensity of workers. As an auxiliary treatment tool, rehabilitation robots should have rich and effective motion modes. The exercise mode should be adaptable for patients with different conditions and different recovery periods. To improve the accuracy of human-computer interaction of ankle joint rehabilitation robots (AJRR), this study proposes a man-machine collaboration model of an EEG-driven AJRR. The model mainly expands from two levels (1) to establish the connection between EEG and intention so as to identify the intention. In the recognition process, first feature extraction is given on the preprocessed EEG. Convolutional neural network (CNN) is selected to extract the deep features of the EEG signal, and support vector machine (SVM) is used for classifying the deep features, thereby realizing intent recognition. (2) The result of intention recognition is input to the human-computer interaction (HCI) system, which controls the movement of the rehabilitation robot after receiving the instruction. This study truly realizes patient-oriented rehabilitation training. Experiments show that the human-machine collaboration model used can show higher accuracy of intention recognition, thereby increasing the satisfaction of using AJRR.

show abstract

Medical Robotics

Cited by 8 publications

References 22 publications

Design of Robot Manipulators and Functional Classification of Medical Robots

Design of Robot Manipulators and Functional Classification of Medical Robots

Autonomous path planning for robot‐assisted pelvic fracture closed reduction with collision avoidance

A Novel Human-Machine Collaboration Model of an Ankle Joint Rehabilitation Robot Driven by EEG Signals

Contact Info

Product

Resources

About