Force measurement capability for robotic assisted minimally invasive surgery systems

An automated laparoscopic instrument capable of non-invasive measurement of tip/tissue interaction forces for direct application in robotic assisted minimally invasive surgery systems_ is introduced in this paper. It has the capability to measure normal grasping forces as well as lateral interaction forces without any sensor mounted on the tip jaws. Further to non-invasive actuation of the tip, the proposed instrument is also able to change the grasping direction during surgical operation. Modular design of the instrument allows conversion between surgical modalities (e.g., grasping, cutting, and dissecting). The main focus of this paper is on evaluation of the grasping force capability of the proposed instrument. The mathematical formulation of fenestrated insert is presented and its non-linear behaviour is studied. In order to measure the stiffness of soft tissues, a device was developed that is also described in this paper. Tissue characterisation experiments were conducted and results are presented and analysed here. The experimental results verify the capability of the proposed instrument in accurately measuring grasping forces and in characterising artificial tissue samples of varying stiffness.<br /

Sıkma Kuvveti Uygulamadan Değişken Şekilli Yumuşak Dokuların Kavranması İçin Yeni Bir Laparoskopik Tutucu Tasarımı ve Uygulanabilirlik Testleri

Cerrahlar, Laparoskopik cerrahi sırasında yumuşak dokuları tutmak ve hareket ettirmek için tutucular kullanmaktadır. Bu tutucuların kavrama çeneleri, dokuların kaymaması için değişik yapılarda dişli yapıyasahiptirler. Dokuların tutucu çeneler arasında sıkıştırılması sonucunda doku hasarı riski oluşmaktadır. Bu çalışmada bu riskin ortadan kaldırılması için Bernoulli prensibi kullanılarak çalışan, dokuları sıkmadankaldırabilen yeni bir Laparoskopik tutucu tasarlanıp üretilerek deneysel çalışma ile uygulanabilirlik testleri yapılmıştır. Tutucu, doku ile arasında Bernoulli prensibi ile yüksek hava akış hızı ile vakum oluşturularakçalışmaktadır. Kaldırılan dokuların kuvvetli hava jetinden zarar görmemesi için eksenel yönde akan havanın akış yönünü değiştirmek amacıyla tutucu yüzey merkezine deflektör yerleştirilmiştir. Çalışma, Bernoulli prensibi ile çalışan bir tutucunun yumuşak ve esnek dokuların sıkıştırılmadan kaldırılması ve hareketi için uygulanabileceğini göstermiştir

Distance‐based time series classification approach for task recognition with application in surgical robot autonomy

BackgroundRobotic‐assisted surgery allows surgeons to perform many types of complex operations with greater precision than is possible with conventional surgery. Despite these advantages, in current systems, a surgeon should communicate with the device directly and manually. To allow the robot to adjust parameters such as camera position, the system needs to know automatically what task the surgeon is performing.MethodsA distance‐based time series classification framework has been developed which measures dynamic time warping distance between temporal trajectory data of robot arms and classifies surgical tasks and gestures using a k‐nearest neighbor algorithm.ResultsResults on real robotic surgery data show that the proposed framework outperformed state‐of‐the‐art methods by up to 9% across three tasks and by 8% across gestures.ConclusionThe proposed framework is robust and accurate. Therefore, it can be used to develop adaptive control systems that will be more responsive to surgeons’ needs by identifying next movements of the surgeon. Copyright © 2016 John Wiley & Sons, Ltd.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138333/1/rcs1766.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138333/2/rcs1766_am.pd

Force/position-based modular system for minimally invasive surgery,”

Abstract-The limitations of minimally invasive surgery include the inability to sense forces exerted by the instruments on tissue and the limited visual cues available through the endoscope. A modular laparoscopic instrument capable of measuring force and position has been designed to address these limitations. Novel image-based position tracking software has been developed and integrated within a graphical user interface. This modular system is low cost, versatile, and could be used for training, localization of critical features or for guidance during surgical procedures

Automated robot‐assisted surgical skill evaluation: Predictive analytics approach

BackgroundSurgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot‐assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predictive framework for objective skill assessment based on movement trajectory data. Our aim is to build a classification framework to automatically evaluate the performance of surgeons with different levels of expertise.MethodsEight global movement features are extracted from movement trajectory data captured by a da Vinci robot for surgeons with two levels of expertise – novice and expert. Three classification methods – k‐nearest neighbours, logistic regression and support vector machines – are applied.ResultsThe result shows that the proposed framework can classify surgeons’ expertise as novice or expert with an accuracy of 82.3% for knot tying and 89.9% for a suturing task.ConclusionThis study demonstrates and evaluates the ability of machine learning methods to automatically classify expert and novice surgeons using global movement features.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141457/1/rcs1850.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/141457/2/rcs1850_am.pd

Relevance of motion-related assessment metrics in laparoscopic surgery

INTRODUCTION: Motion metrics have become an important source of information when addressing the assessment of surgical expertise. However, their direct relationship with the different surgical skills has not been fully explored. The purpose of this study is to investigate the relevance of motion-related metrics in the evaluation processes of basic psychomotor laparoscopic skills, as well as their correlation with the different abilities sought to measure. METHODS: A framework for task definition and metric analysis is proposed. An explorative survey was first conducted with a board of experts to identify metrics to assess basic psychomotor skills. Based on the output of that survey, three novel tasks for surgical assessment were designed. Face and construct validation study was performed, with focus on motion-related metrics. Tasks were performed by 42 participants (16 novices, 22 residents and 4 experts). Movements of the laparoscopic instruments were registered with the TrEndo tracking system and analyzed. RESULTS: Time, path length and depth showed construct validity for all three tasks. Motion smoothness and idle time also showed validity for tasks involving bi-manual coordination and tasks requiring a more tactical approach respectively. Additionally, motion smoothness and average speed showed a high internal consistency, proving them to be the most task-independent of all the metrics analyzed. CONCLUSION: Motion metrics are complementary and valid for assessing basic psychomotor skills, and their relevance depends on the skill being evaluated. A larger clinical implementation, combined with quality performance information, will give more insight on the relevance of the results shown in this study

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