Methods and Tools for Objective Assessment of Psychomotor Skills in Laparoscopic Surgery

Training and assessment paradigms for laparoscopic surgical skills are evolving from traditional mentor–trainee tutorship towards structured, more objective and safer programs. Accreditation of surgeons requires reaching a consensus on metrics and tasks used to assess surgeons’ psychomotor skills. Ongoing development of tracking systems and software solutions has allowed for the expansion of novel training and assessment means in laparoscopy. The current challenge is to adapt and include these systems within training programs, and to exploit their possibilities for evaluation purposes. This paper describes the state of the art in research on measuring and assessing psychomotor laparoscopic skills. It gives an overview on tracking systems as well as on metrics and advanced statistical and machine learning techniques employed for evaluation purposes. The later ones have a potential to be used as an aid in deciding on the surgical competence level, which is an important aspect when accreditation of the surgeons in particular, and patient safety in general, are considered. The prospective of these methods and tools make them complementary means for surgical assessment of motor skills, especially in the early stages of training. Successful examples such as the Fundamentals of Laparoscopic Surgery should help drive a paradigm change to structured curricula based on objective parameters. These may improve the accreditation of new surgeons, as well as optimize their already overloaded training schedules

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

Validation of a Sensorized Instrument-Based Training System for Minimally Invasive Surgery

Minimally invasive surgery training is complicated by the restraints imposed by the surgical environment. A sensorized laparoscopic instrument capable of sensing force in 5 degrees of freedom and position in 6 degrees of freedom was evaluated. Novice and Expert laparoscopists performed a complex minimally invasive surgical task - suturing - using the novel instruments. Their force and position profiles were compared. The novel minimally invasive surgical instrument is construct-valid and capable of detecting differences between novices and experts in a laparoscopic suturing task with respect to force and position. It is also concurrently valid with an existing standard: the Fundamentals of Laparoscopic Skills. Further evaluation is mandated to better understand the ability to predict performance based on force and position as well as the potential for new metrics in minimally invasive surgical education

A Sensorized Instrument for Minimally Invasive Surgery for the Measurement of Forces during Training and Surgery: Development and Applications

The reduced access conditions present in Minimally Invasive Surgery (MIS) affect the feel of interaction forces between the instruments and the tissue being treated. This loss of haptic information compromises the safety of the procedure and must be overcome through training. Haptics in MIS is the subject of extensive research, focused on establishing force feedback mechanisms and developing appropriate sensors. This latter task is complicated by the need to place the sensors as close as possible to the instrument tip, as the measurement of forces outside of the patient\u27s body does not represent the true tool--tissue interaction. Many force sensors have been proposed, but none are yet available for surgery. The objectives of this thesis were to develop a set of instruments capable of measuring tool--tissue force information in MIS, and to evaluate the usefulness of force information during surgery and for training and skills assessment. To address these objectives, a set of laparoscopic instruments was developed that can measure instrument position and tool--tissue interaction forces in multiple degrees of freedom. Different design iterations and the work performed towards the development of a sterilizable instrument are presented. Several experiments were performed using these instruments to establish the usefulness of force information in surgery and training. The results showed that the combination of force and position information can be used in the development of realistic tissue models or haptic interfaces specifically designed for MIS. This information is also valuable in order to create tactile maps to assist in the identification of areas of different stiffness. The real-time measurement of forces allows visual force feedback to be presented to the surgeon. When applied to training scenarios, the results show that experience level correlates better with force-based metrics than those currently used in training simulators. The proposed metrics can be automatically computed, are completely objective, and measure important aspects of performance. The primary contribution of this thesis is the design and development of highly versatile instruments capable of measuring force and position during surgery. A second contribution establishes the importance and usefulness of force data during skills assessment, training and surgery

A Cost-Effective and Smart Sensing Tissue-like Testbed for Surgical Training

A low-cost tissue-like testbed with six nodes of varying stiffness was developed for surgical training to provide pressure and force feedback data through image reception to human operators. Using SolidWorks, a 3D model of the box trainer housing was created. A pad for the distribution of smartsensing nodes and microcontroller connections was designed with open spaces for the respective components. The pad was 3D-printed with PLA filament. Flat piezoelectric pressure sensors were fabricated with conductive materials and velostat sensor material. Using static and dynamic analyses, three top sensors were chosen to be used in three pressure sensing nodes. A calibration process was performed on the pressure sensors to find the linear relationship between voltage and pressure, which was then used to create a conversion equation for each sensor. These equations were used to collect data at the three pressure sensing nodes on the silicone testbed pad. Conductive TPU filament was used to 3D-print vertical force sensors, which were designed using SolidWorks. The force sensors were calibrated with a squeezing mechanism to find a relationship between voltage and force and to subsequently develop a conversion equation for each sensor. We used these equations to collect force data from the three force sensing nodes on the testbed pad. Through static and dynamic analyses, the force sensors were found to be functional, but to need improvements in accuracy. The mechatronic system was designed and developed to integrate all six sensors and to collect data from the testbed pad using an Arduino microcontroller. The flat pressure and vertical force sensors were embedded in each node to measure the pressure and force that occurs during the deformation of the six nodes. Data was collected and imported into MATLAB. This data was used in displaying pressure and force mapping of the nodes over a live video of the silicone pad. Pressure and force mapping was realized by drawing color-coded circles on each of the six nodes that correspond to a range of force or pressure values. From this development, the surgical testbed provides multi-stiffness tissue training with live pressure and force mapping overlaid on a live video of the emulated surgical field

Haptics in Robot-Assisted Surgery: Challenges and Benefits

Robotic surgery is transforming the current surgical practice, not only by improving the conventional surgical methods but also by introducing innovative robot-enhanced approaches that broaden the capabilities of clinicians. Being mainly of man-machine collaborative type, surgical robots are seen as media that transfer pre- and intra-operative information to the operator and reproduce his/her motion, with appropriate filtering, scaling, or limitation, to physically interact with the patient. The field, however, is far from maturity and, more critically, is still a subject of controversy in medical communities. Limited or absent haptic feedback is reputed to be among reasons that impede further spread of surgical robots. In this paper objectives and challenges of deploying haptic technologies in surgical robotics is discussed and a systematic review is performed on works that have studied the effects of providing haptic information to the users in major branches of robotic surgery. It has been tried to encompass both classical works and the state of the art approaches, aiming at delivering a comprehensive and balanced survey both for researchers starting their work in this field and for the experts

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots

Optical Fibre-based Force Sensing Needle Driver for Minimally Invasive Surgery

Minimally invasive surgery has been limited from its inception by insufficient haptic feedback to surgeons. The loss of haptic information threatens patients safety and results in longer operation times. To address this problem, various force sensing systems have been developed to provide information about tool–tissue interaction forces. However, the provided results for axial and grasping forces have been inaccurate in most of these studies due to considerable amount of error and uncertainty in their force acquisition method. Furthermore, sterilizability of the sensorized instruments plays a pivotal role in accurate measurement of forces inside a patient\u27s body. Therefore, the objective of this thesis was to develop a sterilizable needle-driver type grasper using fibre Bragg gratings. In order to measure more accurate and reliable tool–tissue interaction forces, optical force sensors were integrated in the grasper jaw to measure axial and grasping forces directly at their exertion point on the tool tip. Two sets of sensor prototypes were developed to prove the feasibility of proposed concept. Implementation of this concept into a needle-driver instrument resulted in the final proposed model of the sensorized laparoscopic instrument. Fibre Bragg gratings were used for measuring forces due to their many advantages for this application such as small size, sterilizability and high sensitivity. Visual force feedback was provided for users based on the acquired real-time force data. Improvement and consideration points related to the current work were identified and potential areas to continue this project in the future are discussed

A Survey on the Current Status and Future Challenges Towards Objective Skills Assessment in Endovascular Surgery

Minimally-invasive endovascular interventions have evolved rapidly over the past decade, facilitated by breakthroughs in medical imaging and sensing, instrumentation and most recently robotics. Catheter based operations are potentially safer and applicable to a wider patient population due to the reduced comorbidity. As a result endovascular surgery has become the preferred treatment option for conditions previously treated with open surgery and as such the number of patients undergoing endovascular interventions is increasing every year. This fact coupled with a proclivity for reduced working hours, results in a requirement for efficient training and assessment of new surgeons, that deviates from the “see one, do one, teach one” model introduced by William Halsted, so that trainees obtain operational expertise in a shorter period. Developing more objective assessment tools based on quantitative metrics is now a recognised need in interventional training and this manuscript reports the current literature for endovascular skills assessment and the associated emerging technologies. A systematic search was performed on PubMed (MEDLINE), Google Scholar, IEEXplore and known journals using the keywords, “endovascular surgery”, “surgical skills”, “endovascular skills”, “surgical training endovascular” and “catheter skills”. Focusing explicitly on endovascular surgical skills, we group related works into three categories based on the metrics used; structured scales and checklists, simulation-based and motion-based metrics. This review highlights the key findings in each category and also provides suggestions for new research opportunities towards fully objective and automated surgical assessment solutions

Skills Assessment in Arthroscopic Surgery by Processing Kinematic, Force, and Bio-signal Data

Arthroscopic surgery is a type of Minimally Invasive Surgery (MIS) performed in human joints, which can be used for diagnostic or treatment purposes. The nature of this type of surgery makes it such that surgeons require extensive training to become experts at performing surgical tasks in tight environments and with reduced force feedback. MIS increases the possibility of erroneous actions, which could result in injury to the patient. Many of these injuries can be prevented by implementing appropriate training and skills assessment methods. Various performance methods, including Global Rating Scales and technical measures, have been proposed in the literature. However, there is still a need to further improve the accuracy of surgical skills assessment and improve its ability to distinguish fine variations in surgical proficiency. The main goal of this thesis is to enhance surgical, and specifically, arthroscopic skills assessment. The optimal assessment method should be objective, distinguish between subjects with different levels of expertise, and be computationally efficient. This thesis proposes a new method of investigating surgical skills by introducing energy expenditure metrics. To this end, two main approaches are pursued: 1) evaluating the kinematics of instrument motion, and 2) exploring the muscle activity of trainees. Mechanical energy expenditure and work are investigated for a variety of laparoscopic and arthroscopic tasks. The results obtained in this thesis demonstrate that expert surgeons expend less energy than novice trainees. The different forms of mechanical energy expenditure were combined through optimization methods and machine learning algorithms. An optimum two-step optimization method for classifying trainees into detailed levels of expertise is proposed that demonstrates an enhanced ability to determine the level of expertise of trainees compared to other published methods. Furthermore, performance metrics are proposed based on electromyography signals of the forearm muscles, which are recorded using a wearable device. These results also demonstrate that the metrics defined based on muscle activity can be used for arthroscopic skills assessment. The energy-based metrics and the muscle activity metrics demonstrated the ability to identify levels of expertise, with accuracy levels as high as 95% and 100%, respectively. The primary contribution of this thesis is the development of novel metrics and assessment methods based on energy expenditure and muscle activity. The methods presented advance our knowledge of the characteristics of dexterous performance and add another perspective to quantifying surgical proficiency