Conceptual framework for the design, implementation and validation of psychomotor skills’ assessment systems in minimally invasive surgery

Las técnicas de cirugía de mínima invasión (CMI) se están consolidando hoy en día como alternativa a la cirugía tradicional, debido a sus numerosos beneficios para los pacientes. Este cambio de paradigma implica que los cirujanos deben aprender una serie de habilidades distintas de aquellas requeridas en cirugía abierta. El entrenamiento y evaluación de estas habilidades se ha convertido en una de las mayores preocupaciones en los programas de formación de cirujanos, debido en gran parte a la presión de una sociedad que exige cirujanos bien preparados y una reducción en el número de errores médicos. Por tanto, se está prestando especial atención a la definición de nuevos programas que permitan el entrenamiento y la evaluación de las habilidades psicomotoras en entornos seguros antes de que los nuevos cirujanos puedan operar sobre pacientes reales. Para tal fin, hospitales y centros de formación están gradualmente incorporando instalaciones de entrenamiento donde los residentes puedan practicar y aprender sin riesgos. Es cada vez más común que estos laboratorios dispongan de simuladores virtuales o simuladores físicos capaces de registrar los movimientos del instrumental de cada residente. Estos simuladores ofrecen una gran variedad de tareas de entrenamiento y evaluación, así como la posibilidad de obtener información objetiva de los ejercicios. Los diferentes estudios de validación llevados a cabo dan muestra de su utilidad; pese a todo, los niveles de evidencia presentados son en muchas ocasiones insuficientes. Lo que es más importante, no existe un consenso claro a la hora de definir qué métricas son más útiles para caracterizar la pericia quirúrgica. El objetivo de esta tesis doctoral es diseñar y validar un marco de trabajo conceptual para la definición y validación de entornos para la evaluación de habilidades en CMI, en base a un modelo en tres fases: pedagógica (tareas y métricas a emplear), tecnológica (tecnologías de adquisición de métricas) y analítica (interpretación de la competencia en base a las métricas). Para tal fin, se describe la implementación práctica de un entorno basado en (1) un sistema de seguimiento de instrumental fundamentado en el análisis del vídeo laparoscópico; y (2) la determinación de la pericia en base a métricas de movimiento del instrumental. Para la fase pedagógica se diseñó e implementó un conjunto de tareas para la evaluación de habilidades psicomotoras básicas, así como una serie de métricas de movimiento. La validación de construcción llevada a cabo sobre ellas mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. Adicionalmente, los resultados obtenidos en la validación de apariencia fueron en general positivos en todos los grupos considerados (noveles, residentes, expertos). Para la fase tecnológica, se introdujo el EVA Tracking System, una solución para el seguimiento del instrumental quirúrgico basado en el análisis del vídeo endoscópico. La precisión del sistema se evaluó a 16,33ppRMS para el seguimiento 2D de la herramienta en la imagen; y a 13mmRMS para el seguimiento espacial de la misma. La validación de construcción con una de las tareas de evaluación mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. La validación concurrente con el TrEndo® Tracking System por su parte presentó valores altos de correlación para 8 de las 9 métricas analizadas. Finalmente, para la fase analítica se comparó el comportamiento de tres clasificadores supervisados a la hora de determinar automáticamente la pericia quirúrgica en base a la información de movimiento del instrumental, basados en aproximaciones lineales (análisis lineal discriminante, LDA), no lineales (máquinas de soporte vectorial, SVM) y difusas (sistemas adaptativos de inferencia neurodifusa, ANFIS). Los resultados muestran que en media SVM presenta un comportamiento ligeramente superior: 78,2% frente a los 71% y 71,7% obtenidos por ANFIS y LDA respectivamente. Sin embargo las diferencias estadísticas medidas entre los tres no fueron demostradas significativas. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la definición de sistemas de evaluación de habilidades para cirugía de mínima invasión, a la utilidad del análisis de vídeo como fuente de información y a la importancia de la información de movimiento de instrumental a la hora de caracterizar la pericia quirúrgica. Basándose en estos cimientos, se han de abrir nuevos campos de investigación que contribuyan a la definición de programas de formación estructurados y objetivos, que puedan garantizar la acreditación de cirujanos sobradamente preparados y promocionen la seguridad del paciente en el quirófano. Abstract Minimally invasive surgery (MIS) techniques have become a standard in many surgical sub-specialties, due to their many benefits for patients. However, this shift in paradigm implies that surgeons must acquire a complete different set of skills than those normally attributed to open surgery. Training and assessment of these skills has become a major concern in surgical learning programmes, especially considering the social demand for better-prepared professionals and for the decrease of medical errors. Therefore, much effort is being put in the definition of structured MIS learning programmes, where practice with real patients in the operating room (OR) can be delayed until the resident can attest for a minimum level of psychomotor competence. To this end, skills’ laboratory settings are being introduced in hospitals and training centres where residents may practice and be assessed on their psychomotor skills. Technological advances in the field of tracking technologies and virtual reality (VR) have enabled the creation of new learning systems such as VR simulators or enhanced box trainers. These systems offer a wide range of tasks, as well as the capability of registering objective data on the trainees’ performance. Validation studies give proof of their usefulness; however, levels of evidence reported are in many cases low. More importantly, there is still no clear consensus on topics such as the optimal metrics that must be used to assess competence, the validity of VR simulation, the portability of tracking technologies into real surgeries (for advanced assessment) or the degree to which the skills measured and obtained in laboratory environments transfer to the OR. The purpose of this PhD is to design and validate a conceptual framework for the definition and validation of MIS assessment environments based on a three-pillared model defining three main stages: pedagogical (tasks and metrics to employ), technological (metric acquisition technologies) and analytical (interpretation of competence based on metrics). To this end, a practical implementation of the framework is presented, focused on (1) a video-based tracking system and (2) the determination of surgical competence based on the laparoscopic instruments’ motionrelated data. The pedagogical stage’s results led to the design and implementation of a set of basic tasks for MIS psychomotor skills’ assessment, as well as the definition of motion analysis parameters (MAPs) to measure performance on said tasks. Validation yielded good construct results for parameters such as time, path length, depth, average speed, average acceleration, economy of area and economy of volume. Additionally, face validation results showed positive acceptance on behalf of the experts, residents and novices. For the technological stage the EVA Tracking System is introduced. EVA provides a solution for tracking laparoscopic instruments from the analysis of the monoscopic video image. Accuracy tests for the system are presented, which yielded an average RMSE of 16.33pp for 2D tracking of the instrument on the image and of 13mm for 3D spatial tracking. A validation experiment was conducted using one of the tasks and the most relevant MAPs. Construct validation showed significant differences for time, path length, depth, average speed, average acceleration, economy of area and economy of volume; especially between novices and residents/experts. More importantly, concurrent validation with the TrEndo® Tracking System presented high correlation values (>0.7) for 8 of the 9 MAPs proposed. Finally, the analytical stage allowed comparing the performance of three different supervised classification strategies in the determination of surgical competence based on motion-related information. The three classifiers were based on linear (linear discriminant analysis, LDA), non-linear (support vector machines, SVM) and fuzzy (adaptive neuro fuzzy inference systems, ANFIS) approaches. Results for SVM show slightly better performance than the other two classifiers: on average, accuracy for LDA, SVM and ANFIS was of 71.7%, 78.2% and 71% respectively. However, when confronted, no statistical significance was found between any of the three. Overall, this PhD corroborates the investigated research hypotheses regarding the definition of MIS assessment systems, the use of endoscopic video analysis as the main source of information and the relevance of motion analysis in the determination of surgical competence. New research fields in the training and assessment of MIS surgeons can be proposed based on these foundations, in order to contribute to the definition of structured and objective learning programmes that guarantee the accreditation of well-prepared professionals and the promotion of patient safety in the OR.

Energy- and environmentally efficient road management: The case of the Spanish motorway network

Transport is responsible for 41% of CO2 emissions in Spain, and around 65% of that figure is due to road traffic. Tolled motorways are currently managed according to economic criteria: minimizing operational costs and maximizing revenues from tolls. Within this framework, this paper develops a new methodology for managing motorways based on a target of maximum energy efficiency. It includes technological and demand-driven policies, which are applied to two case studies. Various conclusions emerge from this study. One is, that the use of intelligent payment systems is recommended; and another, is that the most sustainable policy would involve defining the most efficient strategy for each motorway section, including the maximum use of its capacity, the toll level which attracts the most vehicles, and the optimum speed limit for each type of vehicle.

Technical evaluation of a third generation optical pose tracker for motion analysis and image-guided surgery

Laparoscopic instrument tracking systems are an essential component in image-guided interventions and offer new possibilities to improve and automate objective assessment methods of surgical skills. In this study we present our system design to apply a third generation optical pose tracker (Micron- Tracker®) to laparoscopic practice. A technical evaluation of this design is performed in order to analyze its accuracy in computing the laparoscopic instrument tip position. Results show a stable fluctuation error over the entire analyzed workspace. The relative position errors are 1.776±1.675 mm, 1.817±1.762 mm, 1.854±1.740 mm, 2.455±2.164 mm, 2.545±2.496 mm, 2.764±2.342 mm, 2.512±2.493 mm for distances of 50, 100, 150, 200, 250, 300, and 350 mm, respectively. The accumulated distance error increases with the measured distance. The instrument inclination covered by the system is high, from 90 to 7.5 degrees. The system reports a low positional accuracy for the instrument tip.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Experiences on the specification of algorithms for fire and smoke control in road tunnels

The main objective of ventilation systems in case of fire is the reduction of the possible consequences by achieving the best possible conditions for the evacuation of the users and the intervention of the emergency services. The required immediate transition, from normal to emergency functioning of the ventilation equipments, is being strengthened by the use of automatic and semi-automatic control systems, what reduces the response times through the help to the operators, and the use of pre-defined strategies. A further step consists on the use of closed-loop algorithms, which takes into account not only the initial conditions but their development (air velocity, traffic situation, etc.), optimizing smoke control capacity.

Development of a methodology and tool to evaluate the impact of ICT measures on road transport emissions

The paper presents the main elements of a project entitled ICT-Emissions that aims at developing a novel methodology to evaluate the impact of ICT-related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures. The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. A number of sources are available to the consortium to obtain the necessary input data. Also, experimental campaigns are offered to fill in gaps of information in traffic and emission patterns. The application of the methodology will be demonstrated using commercially available software. However, the methodology is developed in such a way as to enable its implementation by a variety of emission and traffic models. Particular emphasis is given to (a) the correct estimation of driver behaviour, as a result of traffic-related ICT measures, (b) the coverage of a large number of current vehicle technologies, including ICT systems, and (c) near future technologies such as hybrid, plug-in hybrids, and electric vehicles. The innovative combination of traffic, driver, and emission models produces a versatile toolbox that can simulate the impact on energy and CO2 of infrastructure measures (traffic management, dynamic traffic signs, etc.), driver assistance systems and ecosolutions (speed/cruise control, start/stop systems, etc.) or a combination of measures (cooperative systems).The methodology is validated by application in the Turin area and its capacity is further demonstrated by application in real world conditions in Madrid and Rome.

Control motion approach of a lower limb orthosis to reduce energy consumption

By analysing the dynamic principles of the human gait, an economic gait‐control analysis is performed, and passive elements are included to increase the energy efficiency in the motion control of active orthoses. Traditional orthoses use position patterns from the clinical gait analyses (CGAs) of healthy people, which are then de‐normalized and adjusted to each user. These orthoses maintain a very rigid gait, and their energy cosT is very high, reducing the autonomy of the user. First, to take advantage of the inherent dynamics of the legs, a state machine pattern with different gains in eachstate is applied to reduce the actuator energy consumption. Next, different passive elements, such as springs and brakes in the joints, are analysed to further reduce energy consumption. After an off‐line parameter optimization and a heuristic improvement with genetic algorithms, a reduction in energy consumption of 16.8% is obtained by applying a state machine control pattern, and a reduction of 18.9% is obtained by using passive elements. Finally, by combining both strategies, a more natural gait is obtained, and energy consumption is reduced by 24.6%compared with a pure CGA pattern.

Energy consumption and carbon dioxide emissions in rail and road freight transport in Spain: a case study of car carriers and bulk petrochemicals

This article provides a new methodology for estimating fuel consumption and emissions by enabling a correct comparison between freight transportation modes. The approach is developed and integrated as a part of an intelligent transportation system dealing with goods movement. A key issue is related to energy consumption ratios and consequent CO2 emissions. Energy consumption ratios are often used based on transport demand. However, including other ratios based on transport supply can be useful. Furthermore, it is important to indicate which factors are associated with variations in energy consumption and emissions; especially of interest are parameters that have a higher incidence and order of magnitude, in order to fairly compare and understand the difference between transport modes and sub-modes. The study finds that the use of an energy consumption equation can improve the quality of the estimates. The study proposes that coefficients that define the energy consumption equation should be tested to determine market niches and sources of improvement in energy consumption according to the category of vehicles, fuel types used, and classes of products transported.

Unattended motion detection system based on the mammalian retina

Sensing systems in living bodies offer a large variety of possible different configurations and philosophies able to be emulated in artificial sensing systems. Motion detection is one of the areas where different animals adopt different solutions and, in most of the cases, these solutions reflect a very sophisticated form. One of them, the mammalian visual system, presents several advantages with respect to the artificial ones. The main objective of this paper is to present a system, based on this biological structure, able to detect motion, its sense and its characteristics. The configuration adopted responds to the internal structure of the mammalian retina, where just five types of cells arranged in five layers are able to differentiate a large number of characteristics of the image impinging onto it. Its main advantage is that the detection of these properties is based purely on its hardware. A simple unit, based in a previous optical logic cell employed in optical computing, is the basis for emulating the different behaviors of the biological neurons. No software is present and, in this way, no possible interference from outside affects to the final behavior. This type of structure is able to work, once the internal configuration is implemented, without any further attention. Different possibilities are present in the architecture to be presented: detection of motion, of its direction and intensity. Moreover, some other characteristics, as symmetry may be obtained.

Some aspects of amacrine neuron simulation for motion detection

As it is known, there are five types of neurons in the mammalian retinal layer allowing the detection of several important characteristics of the visual image impinging onto the visual system, namely, photoreceptors, horizontal cells, amacrine, bipolar and ganglion cells. And it is a well known fact too, that the amacrine neuron architecture allows a first detection for objects motion, being the most important retinal cell to this function. We have already studied and simulated the Dowling retina model and we have verified that many complex processes in visual detection is performed with the basis of the amacrine cell synaptic connections. This work will show how this structure may be employed for motion detection

Systems and technologies for objective evaluation of technical skills in laparoscopic surgery

Minimally invasive surgery is a highly demanding surgical approach regarding technical requirements for the surgeon, who must be trained in order to perform a safe surgical intervention. Traditional surgical education in minimally invasive surgery is commonly based on subjective criteria to quantify and evaluate surgical abilities, which could be potentially unsafe for the patient. Authors, surgeons and associations are increasingly demanding the development of more objective assessment tools that can accredit surgeons as technically competent. This paper describes the state of the art in objective assessment methods of surgical skills. It gives an overview on assessment systems based on structured checklists and rating scales, surgical simulators, and instrument motion analysis. As a future work, an objective and automatic assessment method of surgical skills should be standardized as a means towards proficiency-based curricula for training in laparoscopic surgery and its certification.

Depth sensors-based upper limb motion capture system for functional neurorehabilitation

Versatile and accurate motion capture systems, with the required properties to be integrated within both clinical and domiciliary environments, would represent a significant advance in following the progress of the patients as well as in allowing the incorporation of new data exploitation and analysis methods to enhance the functional neurorehabilitation therapeutic processes. Besides, these systems would permit the later development of new applications focused on the automatization of the therapeutic tasks in order to increase the therapist/patient ratio, thus decreasing the costs [1]. However, current motion capture systems are not still ready to work within uncontrolled environments.

Comparative study of two laparoscopic instrument tracker designs for motion analysis and image-guided surgery: a technical evaluation

Laparoscopic instrument tracking systems are a key element in image-guided interventions, which requires high accuracy to be used in a real surgical scenario. In addition, these systems are a suitable option for objective assessment of laparoscopic technical skills based on instrument motion analysis. This study presents a new approach that improves the accuracy of a previously presented system, which applies an optical pose tracking system to laparoscopic practice. A design enhancement of the artificial markers placed on the laparoscopic instrument as well as an improvement of the calibration process are presented as a means to achieve more accurate results. A technical evaluation has been performed in order to compare the accuracy between the previous design and the new approach. Results show a remarkable improvement in the fluctuation error throughout the measurement platform. Moreover, the accumulated distance error and the inclination error have been improved. The tilt range covered by the system is the same for both approaches, from 90º to 7.5º. The relative position error is better for the new approach mainly at close distances to the camera system

Supervised classification of minimally invasive surgery psychomotor competence based on instruments motion analysis

Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.

Application of the agency theory for the analysis of performance-based mechanisms in road management

El WCTR es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte, y aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper develops a model based on agency theory to analyze road management systems (under the different contract forms available today) that employ a mechanism of performance indicators to establish the payment of the agent. The base assumption is that of asymmetric information between the principal (Public Authorities) and the agent (contractor) and the risk aversion of this latter. It is assumed that the principal may only measure the agent?s performance indirectly and by means of certain performance indicators that may be verified by the authorities. In this model there is presumed to be a relation between the efforts made by the agent and the performance level measured by the corresponding indicators, though it is also considered that there may be dispersion between both variables that gives rise to a certain degree of randomness in the contract. An analysis of the optimal contract has been made on the basis of this model and in accordance with a series of parameters that characterize the economic environment and the particular conditions of road infrastructure. As a result of the analysis made, it is considered that an optimal contract should generally combine a fixed component and a payment in accordance with the performance level obtained. The higher the risk aversion of the agent and the greater the marginal cost of public funds, the lower the impact of this performance-based payment. By way of conclusion, the system of performance indicators should be as broad as possible but should not overweight those indicators that encompass greater randomness in their results.