Metodologías de modelado, monitorización y asistencia robótica en neurorrehabilitación funcional de extremidad superior

La Organización Mundial de la Salud (OMS) prevé que para el año 2020, el Daño Cerebral Adquirido (DCA) estará entre las 10 causas más comunes de discapacidad. Estas lesiones, dadas sus consecuencias físicas, sensoriales, cognitivas, emocionales y socioeconómicas, cambian dramáticamente la vida de los pacientes y sus familias. Las nuevas técnicas de intervención precoz y el desarrollo de la medicina intensiva en la atención al DCA han mejorado notablemente la probabilidad de supervivencia. Sin embargo, hoy por hoy, las lesiones cerebrales no tienen ningún tratamiento quirúrgico que tenga por objetivo restablecer la funcionalidad perdida, sino que las terapias rehabilitadoras se dirigen hacia la compensación de los déficits producidos. Uno de los objetivos principales de la neurorrehabilitación es, por tanto, dotar al paciente de la capacidad necesaria para ejecutar las Actividades de Vida Diaria (AVDs) necesarias para desarrollar una vida independiente, siendo fundamentales aquellas en las que la Extremidad Superior (ES) está directamente implicada, dada su gran importancia a la hora de la manipulación de objetos. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma centrado en ofrecer una práctica personalizada, monitorizada y ubicua con una valoración continua de la eficacia y de la eficiencia de los procedimientos y con capacidad de generar conocimientos que impulsen la ruptura del paradigma de actual. Los nuevos objetivos consistirán en minimizar el impacto de las enfermedades que afectan a la capacidad funcional de las personas, disminuir el tiempo de incapacidad y permitir una gestión más eficiente de los recursos. Estos objetivos clínicos, de gran impacto socio-económico, sólo pueden alcanzarse desde una apuesta decidida en nuevas tecnologías, metodologías y algoritmos capaces de ocasionar la ruptura tecnológica necesaria que permita superar las barreras que hasta el momento han impedido la penetración tecnológica en el campo de la rehabilitación de manera universal. De esta forma, los trabajos y resultados alcanzados en la Tesis son los siguientes: 1. Modelado de AVDs: como paso previo a la incorporación de ayudas tecnológicas al proceso rehabilitador, se hace necesaria una primera fase de modelado y formalización del conocimiento asociado a la ejecución de las actividades que se realizan como parte de la terapia. En particular, las tareas más complejas y a su vez con mayor repercusión terapéutica son las AVDs, cuya formalización permitirá disponer de modelos de movimiento sanos que actuarán de referencia para futuros desarrollos tecnológicos dirigidos a personas con DCA. Siguiendo una metodología basada en diagramas de estados UML se han modelado las AVDs 'servir agua de una jarra' y 'coger un botella' 2. Monitorización ubícua del movimiento de la ES: se ha diseñado, desarrollado y validado un sistema de adquisición de movimiento basado en tecnología inercial que mejora las limitaciones de los dispositivos comerciales actuales (coste muy elevado e incapacidad para trabajar en entornos no controlados); los altos coeficientes de correlación y los bajos niveles de error obtenidos en los corregistros llevados a cabo con el sistema comercial BTS SMART-D demuestran la alta precisión del sistema. También se ha realizado un trabajo de investigación exploratorio de un sistema de captura de movimiento de coste muy reducido basado en visión estereoscópica, habiéndose detectado los puntos clave donde se hace necesario incidir desde un punto de vista tecnológico para su incorporación en un entorno real 3. Resolución del Problema Cinemático Inverso (PCI): se ha diseñado, desarrollado y validado una solución al PCI cuando el manipulador se corresponde con una ES humana estudiándose 2 posibles alternativas, una basada en la utilización de un Perceptrón Multicapa (PMC) y otra basada en sistemas Artificial Neuro-Fuzzy Inference Systems (ANFIS). La validación, llevada a cabo utilizando información relativa a los modelos disponibles de AVDs, indica que una solución basada en un PMC con 3 neuronas en la capa de entrada, una capa oculta también de 3 neuronas y una capa de salida con tantas neuronas como Grados de Libertad (GdLs) tenga el modelo de la ES, proporciona resultados, tanto de precisión como de tiempo de cálculo, que la hacen idónea para trabajar en sistemas con requisitos de tiempo real 4. Control inteligente assisted-as-needed: se ha diseñado, desarrollado y validado un algoritmo de control assisted-as-needed para una ortesis robótica con capacidades de actuación anticipatoria de la que existe un prototipo implementado en la actualidad. Los resultados obtenidos demuestran cómo el sistema es capaz de adaptarse al perfil disfuncional del paciente activando la ayuda en instantes anteriores a la ocurrencia de movimientos incorrectos. Esta estrategia implica un aumento en la participación del paciente y, por tanto, en su actividad muscular, fomentándose los procesos la plasticidad cerebral responsables del reaprendizaje o readaptación motora 5. Simuladores robóticos para planificación: se propone la utilización de un simulador robótico assisted-as-needed como herramienta de planificación de sesiones de rehabilitación personalizadas y con un objetivo clínico marcado en las que interviene una ortesis robotizada. Los resultados obtenidos evidencian como, tras la ejecución de ciertos algoritmos sencillos, es posible seleccionar automáticamente una configuración para el algoritmo de control assisted-as-needed que consigue que la ortesis se adapte a los criterios establecidos desde un punto de vista clínico en función del paciente estudiado. Estos resultados invitan a profundizar en el desarrollo de algoritmos más avanzados de selección de parámetros a partir de baterías de simulaciones Estos trabajos han servido para corroborar las hipótesis de investigación planteadas al inicio de la misma, permitiendo, asimismo, la apertura de nuevas líneas de investigación. Summary The World Health Organization (WHO) predicts that by the year 2020, Acquired Brain Injury (ABI) will be among the ten most common ailments. These injuries dramatically change the life of the patients and their families due to their physical, sensory, cognitive, emotional and socio-economic consequences. New techniques of early intervention and the development of intensive ABI care have noticeably improved the survival rate. However, in spite of these advances, brain injuries still have no surgical or pharmacological treatment to re-establish the lost functions. Neurorehabilitation therapies address this problem by restoring, minimizing or compensating the functional alterations in a person disabled because of a nervous system injury. One of the main objectives of Neurorehabilitation is to provide patients with the capacity to perform specific Activities of the Daily Life (ADL) required for an independent life, especially those in which the Upper Limb (UL) is directly involved due to its great importance in manipulating objects within the patients' environment. The incorporation of new technological aids to the neurorehabilitation process tries to reach a new paradigm focused on offering a personalized, monitored and ubiquitous practise with continuous assessment of both the efficacy and the efficiency of the procedures and with the capacity of generating new knowledge. New targets will be to minimize the impact of the sicknesses affecting the functional capabilitiies of the subjects, to decrease the time of the physical handicap and to allow a more efficient resources handling. These targets, of a great socio-economic impact, can only be achieved by means of new technologies and algorithms able to provoke the technological break needed to beat the barriers that are stopping the universal penetration of the technology in the field of rehabilitation. In this way, this PhD Thesis has achieved the following results: 1. ADL Modeling: as a previous step to the incorporation of technological aids to the neurorehabilitation process, it is necessary a first modelling and formalization phase of the knowledge associated to the execution of the activities that are performed as a part of the therapy. In particular, the most complex and therapeutically relevant tasks are the ADLs, whose formalization will produce healthy motion models to be used as a reference for future technological developments. Following a methodology based on UML state-chart diagrams, the ADLs 'serving water from a jar' and 'picking up a bottle' have been modelled 2. Ubiquitous monitoring of the UL movement: it has been designed, developed and validated a motion acquisition system based on inertial technology that improves the limitations of the current devices (high monetary cost and inability of working within uncontrolled environments); the high correlation coefficients and the low error levels obtained throughout several co-registration sessions with the commercial sys- tem BTS SMART-D show the high precision of the system. Besides an exploration of a very low cost stereoscopic vision-based motion capture system has been carried out and the key points where it is necessary to insist from a technological point of view have been detected 3. Inverse Kinematics (IK) problem solving: a solution to the IK problem has been proposed for a manipulator that corresponds to a human UL. This solution has been faced by means of two different alternatives, one based on a Mulilayer Perceptron (MLP) and another based on Artificial Neuro-Fuzzy Inference Systems (ANFIS). The validation of these solutions, carried out using the information regarding the previously generated motion models, indicate that a MLP-based solution, with an architecture consisting in 3 neurons in the input layer, one hidden layer of 3 neurons and an output layer with as many neurons as the number of Degrees of Freedom (DoFs) that the UL model has, is the one that provides the best results both in terms of precission and in terms of processing time, making in idoneous to be integrated within a system with real time restrictions 4. Assisted-as-needed intelligent control: an assisted-as-needed control algorithm with anticipatory actuation capabilities has been designed, developed and validated for a robotic orthosis of which there is an already implemented prototype. Obtained results demonstrate that the control system is able to adapt to the dysfunctional profile of the patient by triggering the assistance right before an incorrect movement is going to take place. This strategy implies an increase in the participation of the patients and in his or her muscle activity, encouraging the neural plasticity processes in charge of the motor learning 5. Planification with a robotic simulator: in this work a robotic simulator is proposed as a planification tool for personalized rehabilitation sessions under a certain clinical criterium. Obtained results indicate that, after the execution of simple parameter selection algorithms, it is possible to automatically choose a specific configuration that makes the assisted-as-needed control algorithm to adapt both to the clinical criteria and to the patient. These results invite researchers to work in the development of more complex parameter selection algorithms departing from simulation batteries Obtained results have been useful to corroborate the hypotheses set out at the beginning of this PhD Thesis. Besides, they have allowed the creation of new research lines in all the studied application fields.

A computational model coupling mechanics and electrophysiology in spinal cord injury

Traumatic brain injury and spinal cord injury have recently been put under the spotlight as major causes of death and disability in the developed world. Despite the important ongoing experimental and modeling campaigns aimed at understanding the mechanics of tissue and cell damage typically observed in such events, the differenti- ated roles of strain, stress and their corresponding loading rates on the damage level itself remain unclear. More specif- ically, the direct relations between brain and spinal cord tis- sue or cell damage, and electrophysiological functions are still to be unraveled. Whereas mechanical modeling efforts are focusing mainly on stress distribution and mechanistic- based damage criteria, simulated function-based damage cri- teria are still missing. Here, we propose a new multiscale model of myelinated axon associating electrophysiological impairment to structural damage as a function of strain and strain rate. This multiscale approach provides a new framework for damage evaluation directly relating neuron mechanics and electrophysiological properties, thus provid- ing a link between mechanical trauma and subsequent func- tional deficits.

Dysfunctional profile for patients in physical neurorehabilitation of upper limb

This paper proposes a first approach to Objective Motor Assessment (OMA) methodology. Also, it introduces the Dysfunctional profile (DP) concept. DP consists of a data matrix characterizing the Upper Limb (UL) physical alterations of a patient with Acquired Brain Injury (ABI) during the rehabilitation process. This research is based on the comparison methology of UL movement between subjects with ABI and healthy subjects as part of OMA. The purpose of this comparison is to classify subjects according to their motor control and subsequently issue a functional assessment of the movement. For this purpose Artificial Neural Networks (ANN) have been used to classify patients. Different network structures are tested. The obtained classification accuracy was 95.65%. This result allows the use of ANNs as a viable option for dysfunctional assessment. This work can be considered a pilot study for further research to corroborate these results.

AMELIE: Authoring Multimedia-Enhanced Learning Interactive Environment for e-Health Contents

This paper presents the AMELIE Authoring Tool for e-health applications. AMELIE provides the means for creating video-based contents with a focus on e-learning and telerehabilitation processes. The main core of AMELIE lies in the efficient exploitation of raw multimedia resources, which may be already available at clinical centers or recorded ad hoc for learning purposes by health professionals. Three real use cases scenarios involving different target users are presented: (1) cognitive skills? training of surgeons in minimally invasive surgery (medical professionals), (2) training of informal carers for elderly home assistance and (3) cognitive rehabilitation of patients with acquired brain injury. Preliminary validation in the field of surgery hints at the potential of AMELIE; and its versatility in different medical applications is patent from the use cases described. Regardless, new validation studies are planned in the three main application areas identified in this work.

Brain structures identification based on feature descriptor

Traumatic Brain Injury -TBI- -1- is defined as an acute event that causes certain damage to areas of the brain. TBI may result in a significant impairment of an individuals physical, cognitive and psychosocial functioning. The main consequence of TBI is a dramatic change in the individuals daily life involving a profound disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges of TBI Neuroimaging is to develop robust automated image analysis methods to detect signatures of TBI, such as: hyper-intensity areas, changes in image contrast and in brain shape. The final goal of this research is to develop a method to identify the altered brain structures by automatically detecting landmarks on the image where signal changes and to provide comprehensive information to the clinician about them. These landmarks identify injured structures by co-registering the patient?s image with an atlas where landmarks have been previously detected. The research work has been initiated by identifying brain structures on healthy subjects to validate the proposed method. Later, this method will be used to identify modified structures on TBI imaging studies.

Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

Monitorización y optimización de terapias de tele-neurorrehabilitación cognitiva

El Daño Cerebral Adquirido (DCA) se define como una lesión cerebral que ocurre después del nacimiento y que no guarda relación con defectos congénitos o enfermedades degenerativas. En el cerebro, se llevan a cabo las funciones mentales superiores como la atención, la memoria, las funciones ejecutivas y el lenguaje, consideradas pre-requisitos básicos de la inteligencia. Sea cual sea su causa, todo daño cerebral puede afectar a una o varias de estas funciones, de ahí la gravedad del problema. A pesar de los avances en nuevas técnicas de intervención precoz y el desarrollo de los cuidados intensivos, las afectaciones cerebrales aún no tienen tratamiento ni quirúrgico ni farmacológico que permita una restitución de las funciones perdidas. Los tratamientos de neurorrehabilitación cognitiva y funcional pretenden, por tanto, la minimización o compensación de las alteraciones ocasionadas por una lesión en el sistema nervioso. En concreto, la rehabilitación cognitiva se define como el proceso en el que personas que han sufrido un daño cerebral trabajan de manera conjunta con profesionales de la salud para remediar o aliviar los déficits cognitivos surgidos como consecuencia de un episodio neurológico. Esto se consigue gracias a la naturaleza plástica del sistema nervioso, donde el cerebro es capaz de reconfigurar sus conexiones neuronales, tanto creando nuevas como modificando las ya existentes. Durante los últimos años hemos visto una transformación de la sociedad, en lo que se ha denominado "sociedad de la información", cuyo pilar básico son las Tecnologías de la Información y las Comunicaciones (TIC). La aplicación de estas tecnologías en medicina ha revolucionado la manera en que se proveen los servicios sanitarios. Así, donde tecnología y medicina se mezclan, la telerrehabilitación se define como la rehabilitación a distancia, ayudando a extender los servicios de rehabilitación más allá de los centros hospitalarios, rompiendo las barreras geográficas, mejorando la eficiencia de los procesos y monitorizando en todo momento el estado y evolución del paciente. En este contexto, el objetivo general de la presente tesis es mejorar la rehabilitación neuropsicológica de pacientes que sufren alteraciones cognitivas, mediante el diseño, desarrollo y validación de un sistema de telemedicina que incorpora las TIC para avanzar hacia un nuevo paradigma personalizado, ubicuo y ecológico. Para conseguirlo, se han definido los siguientes objetivos específicos: • Analizar y modelar un sistema de telerrehabilitación, mediante la definición de objetivos y requisitos de usuario para diseñar las diferentes funcionalidades necesarias. • Definir una arquitectura de telerrehabilitación escalable para la prestación de diferentes servicios que agrupe las funcionalidades necesarias en módulos. • Diseñar y desarrollar la plataforma de telerrehabilitación, incluida la interfaz de usuario, creando diferentes roles de usuario con sus propias funcionalidades. • Desarrollar de un módulo de análisis de datos para extraer conocimiento basado en los resultados históricos de las sesiones de rehabilitación almacenadas en el sistema. • Evaluación de los resultados obtenidos por los pacientes después del programa de rehabilitación, obteniendo conclusiones sobre los beneficios del servicio implementado. • Evaluación técnica de la plataforma de telerrehabilitación, así como su usabilidad y la relación coste/beneficio. • Integración de un dispositivo de eye-tracking que permita la monitorización de la atención visual mientras los pacientes ejecutan tareas de neurorrehabilitación. •Diseño y desarrollo de un entorno de monitorización que permita obtener patrones de atención visual. Como resumen de los resultados obtenidos, se ha desarrollado y validado técnicamente la plataforma de telerrehabilitación cognitiva, demostrando la mejora en la eficiencia de los procesos, sin que esto resulte en una reducción de la eficacia del tratamiento. Además, se ha llevado a cabo una evaluación de la usabilidad del sistema, con muy buenos resultados. Respecto al módulo de análisis de datos, se ha diseñado y desarrollado un algoritmo que configura y planifica sesiones de rehabilitación para los pacientes, de manera automática, teniendo en cuenta las características específicas de cada paciente. Este algoritmo se ha denominado Intelligent Therapy Assistant (ITA). Los resultados obtenidos por el asistente muestran una mejora tanto en la eficiencia como en la eficacia de los procesos, comparado los resultados obtenidos con los de la planificación manual llevada a cabo por los terapeutas. Por último, se ha integrado con éxito el dispositivo de eye-tracking en la plataforma de telerrehabilitación, llevando a cabo una prueba con pacientes y sujetos control que ha demostrado la viabilidad técnica de la solución, así como la existencia de diferencias en los patrones de atención visual en pacientes con daño cerebral. ABSTRACT Acquired Brain Injury (ABI) is defined as brain damage that suddenly and unexpectedly appears in people’s life, being the main cause of disability in developed countries. The brain is responsible of the higher cognitive functions such as attention, memory, executive functions or language, which are considered basic requirements of the intelligence. Whatever its cause is, every ABI may affects one or several functions, highlighting the severity of the problem. New techniques of early intervention and the development of intensive ABI care have noticeably improved the survival rate. However, despite these advances, brain injuries still have no surgical or pharmacological treatment to re-establish lost functions. Cognitive rehabilitation is defined as a process whereby people with brain injury work together with health service professionals and others to remediate or alleviate cognitive deficits arising from a neurological insult. This is achieved by taking advantage of the plastic nature of the nervous system, where the brain can reconfigure its connections, both creating new ones, and modifying the previously existing. Neuro-rehabilitation aims to optimize the plastic nature by inducing a reorganization of the neural network, based on specific experiences. Personalized interventions from individual impairment profile will be necessary to optimize the remaining resources by potentiating adaptive responses and inhibiting maladaptive changes. In the last years, some applications and software programs have been developed to train or stimulate cognitive functions of different neuropsychological disorders, such as ABI, Alzheimer, psychiatric disorders, attention deficit or hyperactivity disorder (ADHD). The application of technologies into medicine has changed the paradigm. Telemedicine allows improving the quality of clinical services, providing better access to them and helping to break geographical barriers. Moreover, one of the main advantages of telemedicine is the possibility to extend the therapeutic processes beyond the hospital (e.g. patient's home). As a consequence, a reduction of unnecessary costs and a better costs/benefits ratio are achieved, making possible a more efficient use of the available resources In this context, the main objective of this work is to improve neuro-rehabilitation of patients suffering cognitive deficits, by designing, developing and validating a telemedicine system that incorporates ICTs to change this paradigm, making it more personalized, ubiquitous and ecologic. The following specific objectives have been defined: • To analyse and model a tele-rehabilitation system, defining objectives and user requirements to design the different needed functionalities. • To define a scalable tele-rehabilitation architecture to offer different services grouping functionalities into modules. • To design and develop the tele-rehabilitation platform, including the graphic user interface, creating different user roles and permissions. • To develop a data analysis module to extract knowledge based on the historic results from the rehabilitation sessions stored in the system. • To evaluate the obtained results by patients after the rehabilitation program, arising conclusions about the benefits of the implemented service. • To technically evaluate the tele-rehabilitation platform, and its usability and the costs/benefit ratio. • To integrate an eye-tracking device allowing the monitoring of the visual attention while patients execute rehabilitation tasks. •To design and develop a monitoring environment that allows to obtain visual attention patterns. Summarizing the obtained results, the cognitive tele-rehabilitation platform has been developed and evaluated technically, demonstrating the improvements on the efficiency without worsening the efficacy of the process. Besides, a usability evaluation has been carried out, with very good results. Regarding the data analysis module, an algorithm has been designed and developed to automatically select and configure rehabilitation sessions, taking into account the specific characteristics of each patient. This algorithm is called Intelligent Therapy Assistant (ITA). The obtained results show an improvement both in the efficiency and the efficacy of the process, comparing the results obtained by patients when they receive treatments scheduled manually by therapists. Finally, an eye-tracking device has been integrated in the tele-rehabilitation platform, carrying out a study with patients and control subjects demonstrating the technical viability of the developed monitoring environment. First results also show that there are differences between the visual attention patterns between ABI patients and control subjects.

A computational model coupling mechanics and electrophysiology in spinal cord injury

Traumatic brain injury and spinal cord injury have recently been put under the spotlight as major causes of death and disability in the developed world. Despite the important ongoing experimental and modeling campaigns aimed at understanding the mechanics of tissue and cell damage typically observed in such events, the differentiated roles of strain, stress and their corresponding loading rates on the damage level itself remain unclear. More specifically, the direct relations between brain and spinal cord tissue or cell damage, and electrophysiological functions are still to be unraveled. Whereas mechanical modeling efforts are focusing mainly on stress distribution and mechanistic-based damage criteria, simulated function-based damage criteria are still missing. Here, we propose a new multiscale model of myelinated axon associating electrophysiological impairment to structural damage as a function of strain and strain rate. This multiscale approach provides a new framework for damage evaluation directly relating neuron mechanics and electrophysiological properties, thus providing a link between mechanical trauma and subsequent functional deficits

Modelado y Evaluación de Entornos Virtuales Interactivos para Rehabilitación Cognitiva en Daño Cerebral

El Daño Cerebral (DC) se refiere a cualquier lesión producida en el cerebro y que afecta a su funcionalidad. Se ha convertido en una de las principales causas de discapacidad neurológica de las sociedades desarrolladas. Hasta la más sencilla de las actividades y acciones que realizamos en nuestro día a día involucran a los procesos cognitivos. Por ello, la alteración de las funciones cognitivas como consecuencia del DC, limita no sólo la calidad de vida del paciente sino también la de las persona de su entorno. La rehabilitación cognitiva trata de aumentar la autonomía y calidad de vida del paciente minimizando o compensando los desórdenes funciones causados por el episodio de DC. La plasticidad cerebral es una propiedad intrínseca al sistema nervioso humano por la que en función a la experiencia se crean nuevos patrones de conectividad. El propósito de la neurorrehabilitación es precisamente modular esta propiedad intrínseca a partir de ejercicios específicos, los cuales podrían derivar en la recuperación parcial o total de las funciones afectadas. La incorporación de la tecnología a las terapias de rehabilitación ha permitido desarrollar nuevas metodologías de trabajo. Esto ha ayudado a hacer frente a las dificultades de la rehabilitación que los procesos tradicionales no logran abarcar. A pesar del gran avance realizado en los Ãoltimos años, todavía existen debilidades en el proceso de rehabilitación; por ejemplo, la trasferencia a la vida real de las habilidades logradas durante la terapia de rehabilitación, así como su generalización a otras actividades cotidianas. Los entornos virtuales pueden reproducir situaciones cotidianas. Permiten simular, de forma controlada, los requisitos conductuales que encontramos en la vida real. En un contexto terapéutico, puede ser utilizado por el neuropsicólogo para corregir en el paciente comportamientos patológicos no deseados, realizar intervenciones terapéuticas sobre Actividades de Vida Diaria que estimulen conductas adaptativas. A pesar de que las tecnologías actuales tienen potencial suficiente para aportar nuevos beneficios al proceso de rehabilitación, existe cierta reticencia a su incorporación a la clínica diaria. A día de hoy, no se ha podido demostrar que su uso aporte una mejorar significativa con respecto a otro tipo de intervención; en otras palabras, no existe evidencia científica de la eficacia del uso de entornos virtuales interactivos en rehabilitación. En este contexto, la presente Tesis Doctoral trata de abordar los aspectos que mantienen a los entornos virtuales interactivos al margen de la rutina clínica diaria. Se estudian las diferentes etapas del proceso de rehabilitación cognitiva relacionado con la integración y uso de estos entornos: diseño de las actividades, su implementación en el entorno virtual, y finalmente la ejecución por el paciente y análisis de los respectivos datos. Por tanto, los bloques en los que queda dividido el trabajo de investigación expuesto en esta memoria son: 1. Diseño de las AVD. La definición y configuración de los elementos que componen la AVD permite al terapeuta diseñar estrategias de intervención terapéutica para actuar sobre el comportamiento del paciente durante la ejecución de la actividad. En esta parte de la tesis se pretende formalizar el diseño de las AVD de tal forma que el terapeuta pueda explotar el potencial tecnológico de los entornos virtuales interactivos abstrayéndose de la complejidad implícita a la tecnología. Para hacer viable este planteamiento se propone una metodología que permita modelar la definición de las AVD, representar el conocimiento implícito en ellas, y asistir al neuropsicólogo durante el proceso de diseño de la intervención clínica. 2. Entorno virtual interactivo. El gran avance tecnológico producido durante los Ãoltimos años permite reproducir AVD interactivas en un contexto de uso clínico. El objetivo perseguido en esta parte de la Tesis es el de extraer las características potenciales de esta solución tecnológica y aplicarla a las necesidades y requisitos de la rehabilitación cognitiva. Se propone el uso de la tecnología de Vídeo Interactivo para el desarrollo de estos entornos virtuales. Para la evaluación de la misma se realiza un estudio experimental dividido en dos fases con la participación de sujetos sanos y pacientes, donde se valora su idoneidad para ser utilizado en terapias de rehabilitación cognitiva. 3. Monitorización de las AVD. El uso de estos entornos virtuales interactivos expone al paciente ante una gran cantidad de estímulos e interacciones. Este hecho requiere de instrumentos de monitorización avanzado que aporten al terapeuta información objetiva sobre el comportamiento del paciente, lo que le podría permitir por ejemplo evaluar la eficacia del tratamiento. En este apartado se propone el uso de métricas basadas en la atención visual y la interacción con el entorno para conocer datos sobre el comportamiento del paciente durante la AVD. Se desarrolla un sistema de monitorización integrado con el entorno virtual que ofrece los instrumentos necesarios para la evaluación de estas métricas para su uso clínico. La metodología propuesta ha permitido diseñar una AVD basada en la definición de intervenciones terapéuticas. Posteriormente esta AVD has sido implementada mediante la tecnología de vídeo interactivo, creando así el prototipo de un entorno virtual para ser utilizado por pacientes con déficit cognitivo. Los resultados del estudio experimental mediante el cual ha sido evaluado demuestran la robustez y usabilidad del sistema, así como su capacidad para intervenir sobre el comportamiento del paciente. El sistema monitorización que ha sido integrado con el entorno virtual aporta datos objetivos sobre el comportamiento del paciente durante la ejecución de la actividad. Los resultados obtenidos permiten contrastar las hipótesis de investigación planteadas en la Tesis Doctoral, aportando soluciones que pueden ayudar a la integración de los entornos virtuales interactivos en la rutina clínica. Esto abre una nueva vía de investigación y desarrollo que podría suponer un gran progreso y mejora en los procesos de neurorrehabilitación cognitiva en daño cerebral. ABSTRACT Brain injury (BI) refers to medical conditions that occur in the brain, altering its function. It becomes one of the main neurological disabilities in the developed society. Cognitive processes determine individual performance in Activities of Daily Living (ADL), thus, the cognitive disorders after BI result in a loss of autonomy and independence, affecting the patient’s quality of life. Cognitive rehabilitation seeks to increase patients’ autonomy and quality of life minimizing or compensating functional disorders showed by BI patients. Brain plasticity is an intrinsic property of the human nervous system whereby its structure is changed depending on experience. Neurorehabilitation pursuits a precise modulation of this intrinsic property, based on specific exercises to induce functional changes, which could result in partial or total recovery of the affected functions. The new methodologies that can be approached by applying technologies to the rehabilitation process, permit to deal with the difficulties which are out of the scope of the traditional rehabilitation. Despite this huge breakthrough, there are still weaknesses in the rehabilitation process, such as the transferring to the real life those skills reached along the therapy, and its generalization to others daily activities. Virtual environments reproduce daily situations. Behavioural requirements which are similar to those we perceive in real life, are simulated in a controlled way. In these virtual environments the therapist is allowed to interact with patients without even being present, inhibiting unsuitable behaviour patterns, stimulating correct answers throughout the simulation and enhancing stimuli with supplementary information when necessary. Despite the benefits which could be brought to the cognitive rehabilitation by applying the potential of the current technologies, there are barriers for widespread use of interactive virtual environments in clinical routine. At present, the evidence that these technologies bring a significant improvement to the cognitive therapies is limited. In other words, there is no evidence about the efficacy of using virtual environments in rehabilitation. In this context, this work aims to address those issues which keep the virtual environments out of the clinical routine. The stages of the cognitive rehabilitation process, which are related with the use and integration of these environments, are analysed: activities design, its implementation in the virtual environment, and the patient’s performance and the data analysis. Hence, the thesis is comprised of the main chapters that are listed below: 1. ADL Design.Definition and configuration of the elements which comprise the ADL allow the therapist to design intervention strategies to influence over the patient behaviour along the activity performance. This chapter aims to formalise the AVD design in order to help neuropsychologists to make use of the interactive virtual environments’ potential but isolating them from the complexity of the technology. With this purpose a new methodology is proposed as an instrument to model the ADL definition, to manage its implied knowledge and to assist the clinician along the design process of the therapeutic intervention. 2. Interactive virtual environment. Continuous advancements make the technology feasible for re-creating rehabilitation therapies based on ADL. The goal of this stage is to analyse the main features of virtual environments in order to apply them according to the cognitive rehabilitation’s requirements. The interactive video is proposed as the technology to develop virtual environments. Experimental study is carried out to assess the suitability of the interactive video to be used by cognitive rehabilitation. 3. ADL monitoring system. This kind of virtual environments bring patients in front lots of stimuli and interactions. Thus, advanced monitoring instruments are needed to provide therapist with objective information about patient’s behaviour. This thesis chapter propose the use of metrics rely on visual patients’ visual attention and their interactions with the environment. A monitoring system has been developed and integrated with the interactive video-based virtual environment, providing neuropsychologist with the instruments to evaluate the clinical force of this metrics. Therapeutic interventions-based ADL has been designed by using the proposed methodology. Interactive video technology has been used to develop the ADL, resulting in a virtual environment prototype to be use by patients who suffer a cognitive deficits. An experimental study has been performed to evaluate the virtual environment, whose overcomes show the usability and solidity of the system, and also its capacity to have influence over patient’s behaviour. The monitoring system, which has been embedded in the virtual environment, provides objective information about patients’ behaviour along their activity performance. Research hypothesis of the Thesis are proven by the obtained results. They could help to incorporate the interactive virtual environments in the clinical routine. This may be a significant step forward to enhance the cognitive neurorehabilitation processes in brain injury.

Patterns of brain angiogenesis after vascular endothelial growth factor administration in vitro and in vivo

Vascular endothelial growth factor (VEGF) is a secreted endothelial cell mitogen that has been shown to induce vasculogenesis and angiogenesis in many organ systems and tumors. Considering the importance of VEGF to embryonic vascularization and survival, the effects of administered VEGF on developing or adult cerebrovasculature are unknown: can VEGF alter brain angiogenesis or mature cerebrovascular patterns? To examine these questions we exposed fetal, newborn, and adult rat cortical slice explants to graduated doses of recombinant VEGF. The effects of another known angiogenic factor, basic fibroblast growth factor (bFGF), were evaluated in a comparable manner. In addition, we infused VEGF via minipump into the adult cortex. Significant angiogenic effects were found in all VEGF experiments in a dose-responsive manner that were abolished by the addition of VEGF neutralizing antibody. Fetal and newborn explants had a highly complex network of branched vessels that immunoexpressed the flt-1 VEGF receptor, and flk-1 VEGF receptor expression was determined by reverse transcription–PCR. Adult explants had enlarged, dilated vessels that appeared to be an expansion of the existing network. All bFGF-treated explants had substantially fewer vascular profiles. VEGF infusions produced both a remarkable localized neovascularization and, unexpectedly, the expression of flt-1 on reactive astrocytes but not on endothelial cells. The preponderance of neovascularization in vitro and in vivo, however, lacked the blood–brain barrier (BBB) phenotype marker, GLUT-1, suggesting that in brain the angiogenic role of VEGF may differ from a potential BBB functional role, i.e., transport and permeability. VEGF may serve an important capacity in neovascularization or BBB alterations after brain injury.

N-Methyl-d-aspartate antagonists and apoptotic cell death triggered by head trauma in developing rat brain

Morbidity and mortality from head trauma is highest among children. No animal model mimicking traumatic brain injury in children has yet been established, and the mechanisms of neuronal degeneration after traumatic injury to the developing brain are not understood. In infant rats subjected to percussion head trauma, two types of brain damage could be characterized. The first type or primary damage evolved within 4 hr and occurred by an excitotoxic mechanism. The second type or secondary damage evolved within 6–24 hr and occurred by an apoptotic mechanism. Primary damage remained localized to the parietal cortex at the site of impact. Secondary damage affected distant sites such as the cingulate/retrosplenial cortex, subiculum, frontal cortex, thalamus and striatum. Secondary apoptotic damage was more severe than primary excitotoxic damage. Morphometric analysis demonstrated that the N-methyl-d-aspartate receptor antagonists 3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonate and dizocilpine protected against primary excitotoxic damage but increased severity of secondary apoptotic damage. 2-Sulfo-α-phenyl-N-tert-butyl-nitrone, a free radical scavenger, did not affect primary excitotoxic damage but mitigated apoptotic damage. These observations demonstrate that apoptosis and not excitotoxicity determine neuropathologic outcome after traumatic injury to the developing brain. Whereas free radical scavengers may prove useful in therapy of head trauma in children, N-methyl-d-aspartate antagonists should be avoided because of their propensity to increase severity of apoptotic damage.

Creating a Web-accessible, point-of-care, team-based information system (PoinTIS): the librarian as publisher*

The Internet has created new opportunities for librarians to develop information systems that are readily accessible at the point of care. This paper describes the multiyear process used to justify, fund, design, develop, promote, and evaluate a rehabilitation prototype of a point-of-care, team-based information system (PoinTIS) and train health care providers to use this prototype for their spinal cord injury and traumatic brain injury patient care and education activities. PoinTIS is a successful model for librarians in the twenty-first century to serve as publishers of information created or used by their parent organizations and to respond to the opportunities for information dissemination provided by recent technological advances.

Discovery of adrenomedullin in rat ischemic cortex and evidence for its role in exacerbating focal brain ischemic damage.

Focal brain ischemia is the most common event leading to stroke in humans. To understand the molecular mechanisms associated with brain ischemia, we applied the technique of mRNA differential display and isolated a gene that encodes a recently discovered peptide, adrenomedullin (AM), which is a member of the calcitonin gene-related peptide (CGRP) family. Using the rat focal stroke model of middle cerebral artery occlusion (MCAO), we determined that AM mRNA expression was significantly increased in the ischemic cortex up to 17.4-fold at 3 h post-MCAO (P < 0.05) and 21.7-fold at 6 h post-MCAO (P < 0.05) and remained elevated for up to 15 days (9.6-fold increase; P < 0.05). Immunohistochemical studies localized AM to ischemic neuronal processes, and radioligand (125I-labeled CGRP) displacement revealed high-affinity (IC50 = 80.3 nmol) binding of AM to CGRP receptors in brain cortex. The cerebrovascular function of AM was studied using synthetic AM microinjected onto rat pial vessels using a cranial window or applied to canine basilar arteries in vitro. AM, applied abluminally, produced dose-dependent relaxation of preconstricted pial vessels (P < 0.05). Intracerebroventricular (but not systemic) AM administration at a high dose (8 nmol), prior to and after MCAO, increased the degree of focal ischemic injury (P < 0.05). The ischemia-induced expression of both AM mRNA and peptide in ischemic cortical neurons, the demonstration of the direct vasodilating effects of the peptide on cerebral vessels, and the ability of AM to exacerbate ischemic brain damage suggests that AM plays a significant role in focal ischemic brain injury.

DUI program as OEF/OIF Veterans Outreach: Descriptive Data from Two Community-Based Outpatient Clinics

Although initially conceived as providing simply the preventive portion of an extended continuum of care for veterans, the Driving Under the Influence (DUI) program has turned out to be an important outreach service for active duty or recently discharged OEF/OIF (Operation Enduring Freedom/Operation Iraqi Freedom) veterans. Veterans receive empirically-based, state-mandated education and therapy under the only Department of Veterans Affairs (VA) - sponsored DUI program in the State of Colorado, with the advantage of having providers who are sensitive to symptoms of Post-Traumatic Stress Disorder (PTSD) and other relevant diagnoses specific to this population, including Traumatic Brain Injury (TBI). In this paper, the rapid growth of this program is described, as well as summary data regarding the completion, discontinuation, and augmentation of services from the original referral concern. Key results indicated that for nearly one third (31.9%) of the OEF/OIF veterans who were enrolled in the DUI program, this was their initial contact with the VA health care system. Furthermore, following their enrollment in the DUI program, more than one fourth (27.6%) were later referred to and attended other VA programs including PTSD rehabilitation and group therapy, anger management, and intensive inpatient or outpatient dual diagnosis programs. These and other findings from this study suggest that the DUI program may be an effective additional pathway for providing treatment that is particularly salient to the distinctive OEF/OIF population; one that may also result in earlier intervention for problem drinking and other problems related to combat. Relevant conclusions discussed herein primarily aim to improve providers' understanding of effective outreach, and to enhance the appropriate linkages between OEF/OIF veterans and existing VA services.