Desenvolvimento de um Sensor Híbrido - Inclinação + EMG - para Aplicações em Robótica e Fisioterapia

Os equipamentos usados para captura de sinais eletromiográficos são, em geral, caros e difíceis de serem usados em ambientes fora de laboratórios. Este trabalho descreve o desenvolvimento de um sensor híbrido capaz de capturar sinais mioelétricos e sinais de inclinação, contando para isso com um par de eletrodos diferenciais e um acelerômetro de três eixos como dispositivos sensores. As informações capturadas pelo sensor híbrido podem ser usadas para análise biomecânica do movimento humano, e todas elas são transmitidas via comunicação Bluetooth, deixando o sensor livre de fios e cabos. O sensor híbrido apresenta aplicações tanto na área de Robótica como Fisioterapia. Na área de Robótica foi usado como um sistema autônomo para comando de uma cadeira de rodas robótica por pessoas com deficiência, através dos movimentos da cabeça do usuário, apresentando bons resultados. Ainda na área de Robótica, foi usado para comandar um pequeno robô com garra, em um projeto de assistência a crianças com deficiências motoras severas. Na área de Fisioterapia apresenta diversas aplicações onde a coleta de sinais mioelétricos é necessária, sendo usado também para detectar a inclinação de membros do corpo em trabalhos fisioterapêuticos. Em seu estado final o sensor híbrido constitui-se de um dispositivo eletrônico portátil, sem fios, pequeno, leve, de grande autonomia, com grande capacidade de cálculo e alta taxa de transmissão de dados. Isso possibilita seu uso fora de laboratórios, ampliando a área de aplicação

Robotic exoskeleton with an assist-as-needed control strategy for gait rehabilitation after stroke

Stroke is a loss of brain function caused by a disturbance on the blood supply to the brain. The main consequence of a stroke is a serious long-term disability, and it affects millions of people around the world every year. Motor recovery after stroke is primarily based on physical therapy and the most common rehabilitation method focuses on the task specific approach. Gait is one of the most important daily life activity affected in stroke victims, leading to poor ambulatory activity. Therefore, much effort has been devoted to improve gait rehabilitation. Traditional gait therapy is mostly based on treadmill training, with patient’s body weight partially supported by a harness system. Physical therapists need to manually assist patients in the correct way to move their legs. However, this technique is usually very exhausting for therapists and, as a result, the training duration is limited by the physical conditions of the therapists themselves. Moreover, multiple therapists are required to assist a single patient on both legs, and it is very difficult to coordinate and properly control the body segments of interest. In order to help physical therapists to improve the rehabilitation process, robotic exoskeletons can come into play. Robotics exoskeletons consist of mechatronic structures attached to subject’s limbs in order to assist or enhance movements. These robotic devices have emerged as a promising approach to restore gait and improve motor function of impaired stroke victims, by applying intensive and repetitive training. However, active subject participation during the therapy is paramount to many of the potential recovery pathways and, therefore, it is an important feature of the gait training. To this end, robotics devices should not impose fixed limb trajectories while patient remains passive. These have been the main motivations for the research of this dissertation. The overall aim was to generate the necessary knowledge to design, develop and validate a novel lower limb robotic exoskeleton and an assist-as-needed therapy for gait rehabilitation in post-stroke patients. Research activities were conducted towards the development of the hardware and the control methods required to prove the concept with a clinical evaluation. The first part of the research was dedicated to design and implement a lightweight robotic exoskeleton with a comfortable embodiment to the user. It was envisioned as a completely actuated device in the sagittal plane, capable of providing the necessary torque to move the hip, knee and ankle joints through the walking process. The device, that does not extend above mid-abdomen and requires nothing to be worn over the shoulders or above the lower back, presumably renders more comfort to the user. Furthermore, the robotic exoskeleton is an autonomous device capable of overground walking, aiming to motivate and engage patients by performing gait rehabilitation in a real environment. The second research part was devoted to implement a control approach that assist the patient only when needed. This method creates a force field that guides patient’s limb in a correct trajectory. In this way, the robotic exoskeleton only applies forces when the patient deviates from the trajectory. The force field provides haptic feedback that is processed by the patient, thus leading to a continuous improvement of the motor functions. Finally, research was conducted to evaluate the robotic exoskeleton and its control approach in a clinical study with post-stroke patients. This study aimed to be a proof-of-concept of all design and implementation applied to a real clinical rehabilitation scenario. Several aspects were evaluated: the robotic exoskeleton control performance, patients’ attitudes and motivation towards the use of the device, patients’ safety and tolerance to the intensive robotic training and the impact of the robotic training on the walking function of the patients. Results have shown that the device is safe, easy to use and have positive impact on walking functions. The patients tolerated the walking therapy very well and were motivated by training with the device. These results motivate further research on overground walking therapy for stroke rehabilitation with the robotic exoskeleton. The work presented in this dissertation comprises all the way from the research to implementation and evaluation of a final device. The technology resulting from the work presented here has been transferred to a spin-o↵ company, which is now commercializing the device in different countries as a research tool to be used in clinical studies.Un accidente cerebrovascular es una pérdida de la función cerebral causada por una perturbación en el suministro sanguíneo al cerebro. La principal consecuencia de esta enfermedad es una grave discapacidad a largo plazo, que afecta a millones de personas en todo el mundo a cada año. La recuperación motora después de un accidente cerebrovascular se basa principalmente en la terapia física, y el método de rehabilitación más frecuente se centra en un entrenamiento específico. La marcha es una de las más importantes actividades de la vida diaria afectada por un accidente cerebrovascular, conduciendo a una capacidad ambulatoria deficiente. Debido a eso, mucho esfuerzo se ha dedicado a la rehabilitación de la marcha. La terapia tradicional de la marcha se basa principalmente en el entrenamiento en cinta rodante, con descarga de peso parcial usando un sistema de arnés. Los fisioterapeutas ayudan manualmente a los pacientes a mover sus piernas en la forma correcta. Sin embargo, esta técnica suele ser muy extenuante para los terapeutas, limitando la duración de la terapia por las condiciones físicas de estos. Además, se requieren múltiples terapeutas para asistir a un solo paciente en ambas piernas, siendo muy difícil de coordinar y controlar adecuadamente los segmentos corporales de interés. Con el fin de ayudar a los terapeutas físicos a mejorar el proceso de rehabilitación, los exosqueletos robóticos pueden ser muy útiles. Los exoesqueletos robóticos consisten en estructuras mecatrónicas conectadas a las extremidades del usuario, con el fin de asistir sus movimientos. Estos dispositivos robóticos han surgido como una forma prometedora de restaurar la marcha y mejorar la función motora en víctimas de accidentes cerebrovasculares, aplicando un entrenamiento intensivo y repetitivo. Sin embargo, la participación activa del paciente en la terapia es primordial para muchas de las posibles vías de recuperación y, por lo tanto, es una característica importante del entrenamiento de la marcha. Para este fin, los dispositivos robóticos no deben imponer trayectorias fijas en las extremidades del paciente mientras este permanece pasivo. Estos desafíos en los procesos de rehabilitación han sido la principal motivación para la investigación en esta tesis doctoral. El objetivo principal es generar los conocimientos necesarios para diseñar, desarrollar y validar un exoesqueleto robótico y una terapia de asistencia bajo demanda para la rehabilitación de la marcha en pacientes tras un accidente cerebrovascular. Actividades de investigación fueron llevadas a cabo para el desarrollo del hardware y de los métodos de control necesarios para una prueba de concepto mediante una evaluación clínica. La primera parte de la investigación fue dedicada a diseñar e implementar un exoesqueleto robótico ligero y cómodo para el usuario. Fue concebido un dispositivo completamente actuado en el plano sagital, capaz de proporcionar el par necesario para mover las articulaciones de la cadera, rodilla y tobillo durante la marcha. El dispositivo no se extiende por encima de mitad del abdomen y no requiere llevar nada sobre los hombros o en el tronco, proporcionando más comodidad al usuario. Además, el exoesqueleto robótico es un dispositivo autónomo capaz de asistir marcha ambulatoria, con el objetivo de motivar a los pacientes por medio de rehabilitación en un entorno real. La segunda parte de la investigación fue dedicada a implementar una estrategia de control para ayudar al paciente bajo demanda. El método crea un campo de fuerzas que guía la extremidad del paciente en la trayectoria correcta. De esta manera, el exoesqueleto robótico sólo aplica fuerzas cuando el paciente se desvía de la trayectoria. El campo de fuerza proporciona retroalimentación háptica que es procesada por el paciente, lo que conduce a una mejora continua de las funciones motoras. Por último, fue llevada a cabo una investigación para evaluar el exoesqueleto robótico y su estrategia de control en un estudio clínico con pacientes que han sufrido un accidente cerebrovascular. Este estudio fue una prueba de concepto del diseño y de la implementación del dispositivo aplicada a un escenario de rehabilitación clínica real. Se evaluaron varios aspectos: el desempeño de la estrategia de control, las actitudes y motivación de los pacientes hacia el uso del dispositivo, la seguridad del paciente y su tolerancia a la terapia robótica intensiva y el impacto de la rehabilitación en la marcha de los pacientes. Los resultados han demostrado que el dispositivo es seguro, fácil de usar y tiene un impacto positivo en la marcha. Los pacientes toleraron la terapia robótica muy bien y estuvieron motivados por el entrenamiento con el dispositivo. Estos resultados motivan a seguir la investigación con el exoesqueleto robótico aplicado a la rehabilitación de marcha en pacientes que han sufrido un accidente cerebrovascular. El trabajo presentado en esta tesis doctoral comprende todo el camino desde la investigación hasta la ejecución y evaluación de un dispositivo terminado. La tecnología resultante del trabajo que aquí se presenta ha sido transferida a una empresa spin-off, que ahora está comercializando el dispositivo en diferentes países como una herramienta de investigación para ser utilizada en estudios clínicos.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Luís Enrique Moreno Lorente.-Secretario: Juan Aranda López.-Vocal: Jose María Azorín Poved

Feedback-error learning control for powered assistive devices

Active orthoses (AOs) are becoming relevant for user-oriented training in gait rehabilitation. This implies efficient responses of AO's low-level controllers with short time modeling for medical applications. This thesis investigates, in an innovative way, the performance of Feedback-Error Learning (FEL) control to time-effectively adapt the AOs' responses to user-oriented trajectories and changes in the dynamics due to the interaction with the user. FEL control comprises a feedback PID controller and a neural network feedforward controller to promptly learn the inverse dynamics of two AOs. It was carried out experiments with able-bodied subjects walking on a treadmill and considering external disturbances to user-AO interaction. Results showed that the FEL control effectively tracked the user-oriented trajectory with position errors between 5% to 7%, and with a mean delay lower than 25 ms. Compared to a single PID control, the FEL control decreased by 16.5% and 90.7% the position error and delay, respectively. Moreover, the feedforward controller was able to learn the inverse dynamics of the two AOs and adapt to variations in the user-oriented trajectories, such as speed and angular range, while the feedback controller compensated for random disturbances. FEL demonstrated to be an efficient low-level controller for controlling AOs during gait rehabilitation.This work has been supported in part by the Fundação para a Ciência e Tecnologia (FCT) with the Reference Scholarship under Grant SFRH/BD/108309/2015, and part by the FEDER Funds through the Programa Operacional Regional do Norte and national funds from FCT with the project SmartOs - Controlo Inteligente de um Sistema Ortótico Ativo e Autónomo - under Grant NORTE-01-0145-FEDER-030386, and by the FEDER Funds through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI)—with the Reference Project under Grant POCI-01-0145-FEDER-006941

Control of an ambulatory exoskeleton with a brain-machine interface for spinal cord injury gait rehabilitation

The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain-machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton-without any weight or balance support-for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation)

Design and control of a robotic exoskeleton form gait rehabilitation

Tesis de Máster escrita para la obtención del Título de Grado en el Official Master in Robotics and Automation. Universidad Carlos III de Madrid. xxiii, 71 p. : il., diagr.Fecha de defensa de la tesis de máster: septiembre del 2013.Exoskeletons are becoming a very powerful tool to help therapists in the rehabilitation of patients who have suffered from neurological conditions, in particular stroke or spinal cord injury. This work presents a robotic exoskeleton designed to assist overground gait training for patients with deficits in gait coordination. The device is a bilateral exoskeleton with six degrees of freedom. It is designed to implement different control strategies. An adaptive trajectory control has been developed to guide the patient’s limb within a desired path, allowing a deviation based on torque of interaction between the user and the exoskeleton. An admittance control strategy allows the robotic platform to capture the user’s movements during assistive training and to replicate them during active training. Experimental results show that the exoskeleton can adapt a pre-recorded gait pattern to the gait pattern of a specific user. Future investigations will evaluate the device in the rehabilitation of patients who have suffered from stroke. A comparative analysis of the effectiveness of different robotic therapies will be proposed.Peer reviewe

Modelagem matemática como ambiente de aprendizagem de estatística na Educação Básica

A presente pesquisa de cunho qualitativo consiste em um estudo de caso que visa experimentar a Modelagem Matemática como Ambiente de Aprendizagem na introdução de conteúdos programáticos de Estatística. A questão que norteou nossa pesquisa foi: “Um Ambiente de Modelagem Matemática favorece a aprendizagem de Estatística na Educação Básica?” Na busca de resposta a essa pergunta, as atividades foram pensadas baseadas no contexto no qual a turma está inserida. Elaboramos uma sequência didática baseada em questionamentos direcionados à reflexão e à investigação. Nesse cenário, o professor tem papel de incentivador da autonomia e capacidade dos alunos produzirem estratégias para resolverem problemas. Trata-se de um plano de natureza aberta, no qual os conhecimentos prévios dos alunos e suas dúvidas têm maior responsabilidade no processo de aprendizagem. Escolhemos a Modelagem Matemática como metodologia, pois ela atende aos objetivos de nosso trabalho, de dar significado à Matemática à medida que a aproximamos da realidade do estudante, desenvolver a autonomia dos alunos, estimulá-los à reflexão e a crítica de fatos oriundos da sociedade. Queremos que os conteúdos sejam introduzidos dentro de um contexto com referência ao dia a dia do educando. Nossa expectativa é que por meio da compreensão da Estatística e de seu papel na sociedade os alunos consigam utilizá-la como ferramenta de análise da realidade vivida. Essa sequência didática foi aplicada em uma turma de 7º ano de Ensino Fundamental de uma escola pública de Sapucaia do Sul – RS. Baseado nesse trabalho, julgamos que utilizar a Modelagem Matemática como Ambiente de Aprendizagem favorece a aprendizagem de Estatística. Acreditamos que os alunos tiveram maior envolvimento nas atividades à medida que a Matemática se tornava mais próxima à realidade deles. Ao longo do trabalho desenvolvido junto aos alunos, percebemos uma evolução na compreensão dos conteúdos abordados. Atribuímos essa evolução ao maior envolvimento dos alunos nos Ambientes de Aprendizagem proporcionados pela Modelagem Matemática.This research consists in a case study which experiments Mathematical Modelling as a Learning Environment to introduce statistical contents. This work seeks to answer the following question: “Does a Mathematical Modelling Environment favors statistical learning on lower secondary education?” In order to answer that, activities were created based on questions that consider the context of the class. In this scenario, the teacher has the role of encouraging autonomy and the students the ability of to producing strategies to solve problems. It is an open plan in which the students' previous knowledge and their doubts have greater responsibility in the learning process. We chose Mathematical Modelling as methodology because it meets the objectives of our work, to give meaning to Mathematics as we approach the reality of the student, to develop students' autonomy, to stimulate them to reflect and critique facts from society. We want the contents to be introduced within a context with reference to the student's day-to-day life. Our expectation is that through the understanding of Statistics and its role in society, students will be able to use it as a tool for analyzing their reality. This didactical sequence was applied on a 7th grade elementary public school class of Sapucaia do Sul – RS. Based on this work, we believe that using Mathematical Modeling as a Learning Environment favors the learning of Statistics. We also believe that students were more involved in activities as Mathematics became closer to their reality. Throughout the work developed with the students, we perceived an evolution in the comprehension of the covered contents. We attribute this evolution to the greater involvement of students in the Learning Environments provided by Mathematical Modeling

Modelagem matemática como ambiente de aprendizagem de estatística na Educação Básica

A presente pesquisa de cunho qualitativo consiste em um estudo de caso que visa experimentar a Modelagem Matemática como Ambiente de Aprendizagem na introdução de conteúdos programáticos de Estatística. A questão que norteou nossa pesquisa foi: “Um Ambiente de Modelagem Matemática favorece a aprendizagem de Estatística na Educação Básica?” Na busca de resposta a essa pergunta, as atividades foram pensadas baseadas no contexto no qual a turma está inserida. Elaboramos uma sequência didática baseada em questionamentos direcionados à reflexão e à investigação. Nesse cenário, o professor tem papel de incentivador da autonomia e capacidade dos alunos produzirem estratégias para resolverem problemas. Trata-se de um plano de natureza aberta, no qual os conhecimentos prévios dos alunos e suas dúvidas têm maior responsabilidade no processo de aprendizagem. Escolhemos a Modelagem Matemática como metodologia, pois ela atende aos objetivos de nosso trabalho, de dar significado à Matemática à medida que a aproximamos da realidade do estudante, desenvolver a autonomia dos alunos, estimulá-los à reflexão e a crítica de fatos oriundos da sociedade. Queremos que os conteúdos sejam introduzidos dentro de um contexto com referência ao dia a dia do educando. Nossa expectativa é que por meio da compreensão da Estatística e de seu papel na sociedade os alunos consigam utilizá-la como ferramenta de análise da realidade vivida. Essa sequência didática foi aplicada em uma turma de 7º ano de Ensino Fundamental de uma escola pública de Sapucaia do Sul – RS. Baseado nesse trabalho, julgamos que utilizar a Modelagem Matemática como Ambiente de Aprendizagem favorece a aprendizagem de Estatística. Acreditamos que os alunos tiveram maior envolvimento nas atividades à medida que a Matemática se tornava mais próxima à realidade deles. Ao longo do trabalho desenvolvido junto aos alunos, percebemos uma evolução na compreensão dos conteúdos abordados. Atribuímos essa evolução ao maior envolvimento dos alunos nos Ambientes de Aprendizagem proporcionados pela Modelagem Matemática.This research consists in a case study which experiments Mathematical Modelling as a Learning Environment to introduce statistical contents. This work seeks to answer the following question: “Does a Mathematical Modelling Environment favors statistical learning on lower secondary education?” In order to answer that, activities were created based on questions that consider the context of the class. In this scenario, the teacher has the role of encouraging autonomy and the students the ability of to producing strategies to solve problems. It is an open plan in which the students' previous knowledge and their doubts have greater responsibility in the learning process. We chose Mathematical Modelling as methodology because it meets the objectives of our work, to give meaning to Mathematics as we approach the reality of the student, to develop students' autonomy, to stimulate them to reflect and critique facts from society. We want the contents to be introduced within a context with reference to the student's day-to-day life. Our expectation is that through the understanding of Statistics and its role in society, students will be able to use it as a tool for analyzing their reality. This didactical sequence was applied on a 7th grade elementary public school class of Sapucaia do Sul – RS. Based on this work, we believe that using Mathematical Modeling as a Learning Environment favors the learning of Statistics. We also believe that students were more involved in activities as Mathematics became closer to their reality. Throughout the work developed with the students, we perceived an evolution in the comprehension of the covered contents. We attribute this evolution to the greater involvement of students in the Learning Environments provided by Mathematical Modeling

BMIs for Motor Rehabilitation: Key Concepts and Challenges

The most recent rehabilitation and diagnostics technologies, including robotics, neuroprostheses, brain-machine interfaces and electromyography systems