Estimation of tool-tissue forces in robot-assisted minimally invasive surgery using neural networks

A new algorithm is proposed to estimate the tool-tissue force interaction in robot-assisted minimally invasive surgery which does not require the use of external force sensing. The proposed method utilizes the current of the motors of the surgical instrument and neural network methods to estimate the force interaction. Offline and online testing is conducted to assess the feasibility of the developed algorithm. Results showed that the developed method has promise in allowing online estimation of tool-tissue force and could thus enable haptic feedback in robotic surgery to be provided

Robot-Assisted Minimally Invasive Surgery-Surgical Robotics in the Data Age

Telesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery (RAMIS), has become the first domain within medicosurgical robotics that achieved a true global clinical adoption. Its relative success (still at a low single-digit percentile total market penetration) roots in the particular human-in-the-loop control, in which the trained surgeon is always kept responsible for the clinical outcome achieved by the robot-actuated invasive tools. Nowadays, this paradigm is challenged by the need for improved surgical performance, traceability, and safety reaching beyond the human capabilities. Partially due to the technical complexity and the financial burden, the adoption of telesurgical robotics has not reached its full potential, by far. Apart from the absolutely market-dominating da Vinci surgical system, there are already 60+ emerging RAMIS robot types, out of which 15 have already achieved some form of regulatory clearance. This article aims to connect the technological advancement with the principles of commercialization, particularly looking at engineering components that are under development and have the potential to bring significant advantages to the clinical practice. Current RAMIS robots often do not exceed the functionalities deriving from their mechatronics, due to the lack of data-driven assistance and smart human–machine collaboration. Computer assistance is gradually gaining more significance within emerging RAMIS systems. Enhanced manipulation capabilities, refined sensors, advanced vision, task-level automation, smart safety features, and data integration mark together the inception of a new era in telesurgical robotics, infiltrated by machine learning (ML) and artificial intelligence (AI) solutions. Observing other domains, it is definite that a key requirement of a robust AI is the good quality data, derived from proper data acquisition and sharing to allow building solutions in real time based on ML. Emerging RAMIS technologies are reviewed both in a historical and a future perspective

A Framework for Tumor Localization in Robot-Assisted Minimally Invasive Surgery

Manual palpation of tissue is frequently used in open surgery, e.g., for localization of tumors and buried vessels and for tissue characterization. The overall objective of this work is to explore how tissue palpation can be performed in Robot-Assisted Minimally Invasive Surgery (RAMIS) using laparoscopic instruments conventionally used in RAMIS. This thesis presents a framework where a surgical tool is moved teleoperatively in a manner analogous to the repetitive pressing motion of a finger during manual palpation. We interpret the changes in parameters due to this motion such as the applied force and the resulting indentation depth to accurately determine the variation in tissue stiffness. This approach requires the sensorization of the laparoscopic tool for force sensing. In our work, we have used a da Vinci needle driver which has been sensorized in our lab at CSTAR for force sensing using Fiber Bragg Grating (FBG). A computer vision algorithm has been developed for 3D surgical tool-tip tracking using the da Vinci \u27s stereo endoscope. This enables us to measure changes in surface indentation resulting from pressing the needle driver on the tissue. The proposed palpation framework is based on the hypothesis that the indentation depth is inversely proportional to the tissue stiffness when a constant pressing force is applied. This was validated in a telemanipulated setup using the da Vinci surgical system with a phantom in which artificial tumors were embedded to represent areas of different stiffnesses. The region with high stiffness representing tumor and region with low stiffness representing healthy tissue showed an average indentation depth change of 5.19 mm and 10.09 mm respectively while maintaining a maximum force of 8N during robot-assisted palpation. These indentation depth variations were then distinguished using the k-means clustering algorithm to classify groups of low and high stiffnesses. The results were presented in a colour-coded map. The unique feature of this framework is its use of a conventional laparoscopic tool and minimal re-design of the existing da Vinci surgical setup. Additional work includes a vision-based algorithm for tracking the motion of the tissue surface such as that of the lung resulting from respiratory and cardiac motion. The extracted motion information was analyzed to characterize the lung tissue stiffness based on the lateral strain variations as the surface inflates and deflates

Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook

Since the emergence of soft robotics around two decades ago, research interest in the field has escalated at a pace. It is fuelled by the industry's appreciation of the wide range of soft materials available that can be used to create highly dexterous robots with adaptability characteristics far beyond that which can be achieved with rigid component devices. The ability, inherent in soft robots, to compliantly adapt to the environment, has significantly sparked interest from the surgical robotics community. This article provides an in-depth overview of recent progress and outlines the remaining challenges in the development of soft robotics for minimally invasive surgery

Modelling, dynamic analysis and control of capsubot systems with stable propulsion for medical and recovery assistances

The growth of medical robots since the mid-1980s has been striking. From a few initial efforts in stereotactic brain surgery, orthopaedics, endoscopic surgery, microsurgery, and other areas, the field has expanded to include commercially marketed, clinically deployed systems, and a robust and exponentially expanding research community. Obscure gastrointestinal (GI) bleeding, Crohn disease, Celiac disease, small bower tumors, and other disorders that occur in the GI tract have always been challenging to be diagnosed and treated due to the inevitable difficulty in accessing such a complex environment within the human body. Robot-assisted minimally invasive surgery has become an choice

Towards an anthropomorphic design of minimally invasive instrumentation for soft tissue robotic surgery

Minimally invasive procedures, such as laparoscopy, have significantly decreased blood loss, postoperative morbidity and length of hospital stay. Robot-assisted Minimally Invasive Surgery (MIS) has offered refined accuracy and more ergonomic instruments for surgeons, further minimizing trauma to the patient [1]. On the other hand, training surgeons in minimally invasive surgical procedures is becoming increasingly long and arduous [2]. In this paper, we outline the rationale of a novel design of instruments for robotic surgery with increased dexterity that will provide more natural manipulation of soft tissues. The proposed system will not only reduce the training time for surgeons but also improve the ergonomics of the procedure. © 2012 Springer-Verlag

Prevalence of haptic feedback in robot-mediated surgery : a systematic review of literature

© 2017 Springer-Verlag. This is a post-peer-review, pre-copyedit version of an article published in Journal of Robotic Surgery. The final authenticated version is available online at: https://doi.org/10.1007/s11701-017-0763-4With the successful uptake and inclusion of robotic systems in minimally invasive surgery and with the increasing application of robotic surgery (RS) in numerous surgical specialities worldwide, there is now a need to develop and enhance the technology further. One such improvement is the implementation and amalgamation of haptic feedback technology into RS which will permit the operating surgeon on the console to receive haptic information on the type of tissue being operated on. The main advantage of using this is to allow the operating surgeon to feel and control the amount of force applied to different tissues during surgery thus minimising the risk of tissue damage due to both the direct and indirect effects of excessive tissue force or tension being applied during RS. We performed a two-rater systematic review to identify the latest developments and potential avenues of improving technology in the application and implementation of haptic feedback technology to the operating surgeon on the console during RS. This review provides a summary of technological enhancements in RS, considering different stages of work, from proof of concept to cadaver tissue testing, surgery in animals, and finally real implementation in surgical practice. We identify that at the time of this review, while there is a unanimous agreement regarding need for haptic and tactile feedback, there are no solutions or products available that address this need. There is a scope and need for new developments in haptic augmentation for robot-mediated surgery with the aim of improving patient care and robotic surgical technology further.Peer reviewe