699 research outputs found

    Exploration of peripheral electrical stimulation adapted as a modulation tool for reciprocal inhibition through the activation of afferent fibers during gait

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    The most accessible manner to perform physical activity and allow locomotion in human beings is walking. This activity is allowed thanks to reciprocal Ia inhibition mechanism, controlled by the spinal and supraspinal inhibitory circuits. The idea of this mechanism is to deactivate the antagonist muscle while the agonist is being contracted, allowing the proper muscle coordination necessary to walk. The interruption of spinal fibers produced after Spinal Cord Injury, disrupt this control on reciprocal Ia inhibition. The result of this lack of control is a co-activation of antagonist muscles generating spasticity of lower limbs which induce walking impairments. The importance of walking recovery for the independence and society re-integration of patient, raise the quantity of emerging walking rehabilitation therapies. One of these therapies, the application of peripheral nerve stimulation, has demonstrated promising results although more studies are necessary. This theory is the base of this Master Thesis which aim is to develop and validate a gait neuromodu- lation platform that induce neuroplasticity of spinal circuits, improving reciprocal Ia inhibition. The idea of the platform is to deliver afferent stimulation into the Common Peroneal Nerve innervating Tibialis Anterior muscle, to induce reciprocal Ia inhibition onto the antagonist Soleus muscle. This platform has been validated in 20 healthy volunteers in order to assess its effectiveness. The first part of the experimental protocol is an off-line analysis of Gait Cycle to evaluate the activation of mus- cles during the different phases of this cycle. Then, there is an assessment of the activity of antagonist muscle previous to the stimulation intervention by using the analysis of soleus H-reflex. Posteri- orly, the afferent stimulation is applied during a 10 minutes treadmill training using three different strategies depending on patient: In-phase stimulation during swing phase, Out-of-phase stimulation during stance phase, and Control strategy to check if stimulation has a real effect. The final processes of experimental protocol are two different assessments of the soleus activity, one immediately after the intervention and other 30 minutes after to evaluate the duration of effects. The results obtained demonstrate that afferent electrical stimulation has a real effect on modulation of reciprocal Ia inhibition. On the one hand, when electrical stimulation is applied during the swing phase, there is an improvement of reciprocal Ia inhibition. On the other hand, when stimulation is delivered during the stance phase, there is a worsening of reciprocal Ia inhibition. These results conclude that afferent electrical stimulation, applied at the swing phase of gait cycle, is a promising strategy to induce reciprocal Ia inhibition in Spinal Cord Injury patients. The induc- tion of this inhibitory circuit will lead to the proper activation of muscles during walking, recovering impaired walkingLa forma más accesible de locomoción y actividad física en los seres humanos es caminar. Esta activi- dad se realiza gracias al mecanismo de inhibición recíproca, controlado por los circuitos inhibitorios espinales y supraespinales. La idea de este mecanismo es desactivar el músculo antagonista mientras se contrae el agonista, permitiendo la adecuada coordinación muscular durante la marcha. La interrupción de las fibras espinales tras una Lesión de la Médula Espinal desajusta el control de la inhibition reciprocal. El resultado de esta falta de control es una co-activación de los músculos antago- nistas generando espasticidad en las extremidades inferiores, lo que genera alteraciones en la marcha. La importancia de la recuperación de la marcha para lograr la independencia y la reintegración del paciente en la sociedad, ha incrementado el número de terapias emergentes en rehabilitación de la marcha. Una de estas terapias, la estimulación del nervio periférico, ha demostrado resultados prom- etedores. Esta teoría es la base de esta Tesis de Máster cuyo objetivo es desarrollar y validar una plataforma de neuromodulación de la marcha que induzca la neuroplasticidad de los circuitos espinales, mejorando los valores de inhibición recíproca. La idea es aplicar estimulación aferente en el Nervio Peroneo Común que inerva el músculo Tibial Anterior para inducir la inhibición recíproca en su músculo antagonista Soleo. Esta plataforma ha sido validada en 20 voluntarios sanos con el fin de evaluar su eficacia. La primera parte del protocolo experimental es un análisis del ciclo de la marcha para evaluar la activación de cada músculo durante las diferentes fases de este ciclo. Luego, previo a la intervención de estimu- lación, hay una evaluación de la actividad del músculo antagonista analizando el reflejo H del soleo. La intervención de estimulación aferente se aplica durante un entrenamiento de marcha con una du- ración de 10 minutos, utilizando tres estrategias diferentes dependiendo del paciente: estimulación ’In-phase’ durante la fase de oscilación, estimulación ’Out-of-phase’ durante la fase de postura, y ’Control’ para comprobar si la estimulación tiene un efecto real. Los procesos finales del protocolo son dos evaluaciones de la actividad del soleo, una inmediatamente después de la intervención y otra 30 minutos después para evaluar la duración de los efectos. Los resultados obtenidos demuestran que la estimulación eléctrica aferente tiene un efecto real en la modulación de la inhibición recíproca. Por un lado, cuando la estimulación eléctrica se aplica durante la fase de oscilación, hay una mejora de la inhibición recíproca. Por otro lado, cuando la estimulación se administra durante la fase de postura, hay un empeoramiento de la inhibición recíproca. Estos resultados concluyen que la estimulación eléctrica aferente, administrada en la fase de oscilación del ciclo de la marcha, es una estrategia prometedora para inducir la inhibición recíproca en pacientes con Lesión de la Médula Espinal. La inducción de este circuito inhibidor generará la adecuada acti- vación de los músculos durante la marcha, recuperando el ciclo de marcha normalLa manera més accessible de locomoció i activitat física en els éssers humans és caminar. Aquesta ac- tivitat es realitza gràcies al mecanisme d’inhibició recíproca, controlat pels circuits inhibitoris espinals i supraespinals. La idea d’aquest mecanisme és desactivar el múscul antagonista mentre es contrau l’agonista, permetent la coordinació muscular adequada durant la marxa. La interrupció de les fibres espinals després d’una lesió medul·lar desajusta el control de la inhibició reciprocal. El resultat d’aquesta manca de control és una coactivació dels músculs antagonistes gen- erant espasticitat a les extremitats inferiors, cosa que genera alteracions a la marxa. La importància de la recuperació de la marxa per a la independència i la reintegració del pacient a la societat, ha incrementat el nombre de teràpies emergents de rehabilitació de la marxa. Una daquestes teràpies, lestimulació del nervi perifèric, ha demostrat resultats prometedors. Aquesta teoria és la base dáquesta Tesi de Màster que té com a objectiu desenvolupar una plataforma de neuromodulació de la marxa que indueixi la neuroplasticitat dels circuits espinals, millorant els valors de inhibició recíproca. La idea és aplicar una estimulació aferent al Nervi Peroneal Comú que inerva el múscul Tibial Anterior per induir la inhibició recíproca al múscul antagonista Soli. Aquesta plataforma ha estat validada en 20 voluntaris sans per avaluar-ne l’eficàcia. La primera part del protocol experimental és una anàlisi del cicle de marxa per avaluar l’activació de cada múscul durant les diferents fases del cicle de la marxa. Després, amb la intervenció d’estimulació prèvia, hi ha una avaluació de l’activitat del múscul antagonista analitzant el reflex H del soli. La inter- venció d’estimulació aferent s’aplica durant un entrenament de marxa amb una durada de 10 min- uts, utilitzant tres estratègies diferents depenent del pacient: estimulació ’In-phase’ durant la fase d’oscil·lació, estimulació ’Out-of-phase’ durant la fase de postura, i ’Control’ per comprovar si la es- timulació té un efecte real. Els processos finals del protocol són dues avaluacions de l’activitat de soli, una immediatament després de la intervenció i una altra 30 minuts després per avaluar la durada dels efectes. Els resultats obtinguts demostren que l’estimulació elèctrica aferent té un efecte real en la modulació de la inhibició recíproca. D’una banda, quan s’aplica l’estimulació elèctrica durant la fase d’oscil·lació, hi ha una millora de la inhibició recíproca. D’altra banda, quan s’administra l’estimulació durant la fase de postura, hi ha un empitjorament de la inhibició recíproca. Aquests resultats conclouen que l’estimulació elèctrica aferent, a la fase d’oscil·lació del cicle de la marxa, és una estratègia prometedora per induir la inhibició recíproca en pacients amb lesió medul·lar. La inducció d’aquest circuit inhibidor generarà a l’activació adequada dels músculs durant la marxa, recuperant el cicle de marxa norma

    Adaptive, fast walking in a biped robot under neuronal control and learning

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    Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks

    Using visual stimuli to enhance gait control

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    Gait control challenges commonly coincide with vestibular dysfunction and there is a long history in using balance and gait activities to enhance functional mobility in this population. While much has been learned using traditional rehabilitation exercises, there is a new line of research emerging that is using visual stimuli in a very specific way to enhance gait control. For example, avatars can be created in an individualized manner to incorporate specific gait characteristics. The avatar could then be used as a visual stimulus to which the patient can synchronize their own gait cycle. This line of research builds upon the rich history of sensorimotor control research in which augmented sensory information (visual, haptic, or auditory) is used to probe, and even enhance, human motor control. This review paper focuses on gait control challenges in patients with vestibular dysfunction, provides a brief historical perspective on how various visual displays have been used to probe sensorimotor and gait control, and offers some recommendations for future research

    Motion representation with spiking neural networks for grasping and manipulation

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    Die Natur bedient sich Millionen von Jahren der Evolution, um adaptive physikalische Systeme mit effizienten Steuerungsstrategien zu erzeugen. Im Gegensatz zur konventionellen Robotik plant der Mensch nicht einfach eine Bewegung und führt sie aus, sondern es gibt eine Kombination aus mehreren Regelkreisen, die zusammenarbeiten, um den Arm zu bewegen und ein Objekt mit der Hand zu greifen. Mit der Forschung an humanoiden und biologisch inspirierten Robotern werden komplexe kinematische Strukturen und komplizierte Aktor- und Sensorsysteme entwickelt. Diese Systeme sind schwierig zu steuern und zu programmieren, und die klassischen Methoden der Robotik können deren Stärken nicht immer optimal ausnutzen. Die neurowissenschaftliche Forschung hat große Fortschritte beim Verständnis der verschiedenen Gehirnregionen und ihrer entsprechenden Funktionen gemacht. Dennoch basieren die meisten Modelle auf groß angelegten Simulationen, die sich auf die Reproduktion der Konnektivität und der statistischen neuronalen Aktivität konzentrieren. Dies öffnet eine Lücke bei der Anwendung verschiedener Paradigmen, um Gehirnmechanismen und Lernprinzipien zu validieren und Funktionsmodelle zur Steuerung von Robotern zu entwickeln. Ein vielversprechendes Paradigma ist die ereignis-basierte Berechnung mit SNNs. SNNs fokussieren sich auf die biologischen Aspekte von Neuronen und replizieren deren Arbeitsweise. Sie sind für spike- basierte Kommunikation ausgelegt und ermöglichen die Erforschung von Mechanismen des Gehirns für das Lernen mittels neuronaler Plastizität. Spike-basierte Kommunikation nutzt hoch parallelisierten Hardware-Optimierungen mittels neuromorpher Chips, die einen geringen Energieverbrauch und schnelle lokale Operationen ermöglichen. In dieser Arbeit werden verschiedene SNNs zur Durchführung von Bewegungss- teuerung für Manipulations- und Greifaufgaben mit einem Roboterarm und einer anthropomorphen Hand vorgestellt. Diese basieren auf biologisch inspirierten funktionalen Modellen des menschlichen Gehirns. Ein Motor-Primitiv wird auf parametrische Weise mit einem Aktivierungsparameter und einer Abbildungsfunktion auf die Roboterkinematik übertragen. Die Topologie des SNNs spiegelt die kinematische Struktur des Roboters wider. Die Steuerung des Roboters erfolgt über das Joint Position Interface. Um komplexe Bewegungen und Verhaltensweisen modellieren zu können, werden die Primitive in verschiedenen Schichten einer Hierarchie angeordnet. Dies ermöglicht die Kombination und Parametrisierung der Primitiven und die Wiederverwendung von einfachen Primitiven für verschiedene Bewegungen. Es gibt verschiedene Aktivierungsmechanismen für den Parameter, der ein Motorprimitiv steuert — willkürliche, rhythmische und reflexartige. Außerdem bestehen verschiedene Möglichkeiten neue Motorprimitive entweder online oder offline zu lernen. Die Bewegung kann entweder als Funktion modelliert oder durch Imitation der menschlichen Ausführung gelernt werden. Die SNNs können in andere Steuerungssysteme integriert oder mit anderen SNNs kombiniert werden. Die Berechnung der inversen Kinematik oder die Validierung von Konfigurationen für die Planung ist nicht erforderlich, da der Motorprimitivraum nur durchführbare Bewegungen hat und keine ungültigen Konfigurationen enthält. Für die Evaluierung wurden folgende Szenarien betrachtet, das Zeigen auf verschiedene Ziele, das Verfolgen einer Trajektorie, das Ausführen von rhythmischen oder sich wiederholenden Bewegungen, das Ausführen von Reflexen und das Greifen von einfachen Objekten. Zusätzlich werden die Modelle des Arms und der Hand kombiniert und erweitert, um die mehrbeinige Fortbewegung als Anwendungsfall der Steuerungsarchitektur mit Motorprimitiven zu modellieren. Als Anwendungen für einen Arm (3 DoFs) wurden die Erzeugung von Zeigebewegungen und das perzeptionsgetriebene Erreichen von Zielen modelliert. Zur Erzeugung von Zeigebewegun- gen wurde ein Basisprimitiv, das auf den Mittelpunkt einer Ebene zeigt, offline mit vier Korrekturprimitiven kombiniert, die eine neue Trajektorie erzeugen. Für das wahrnehmungsgesteuerte Erreichen eines Ziels werden drei Primitive online kombiniert unter Verwendung eines Zielsignals. Als Anwendungen für eine Fünf-Finger-Hand (9 DoFs) wurden individuelle Finger-aktivierungen und Soft-Grasping mit nachgiebiger Steuerung modelliert. Die Greif- bewegungen werden mit Motor-Primitiven in einer Hierarchie modelliert, wobei die Finger-Primitive die Synergien zwischen den Gelenken und die Hand-Primitive die unterschiedlichen Affordanzen zur Koordination der Finger darstellen. Für jeden Finger werden zwei Reflexe hinzugefügt, zum Aktivieren oder Stoppen der Bewegung bei Kontakt und zum Aktivieren der nachgiebigen Steuerung. Dieser Ansatz bietet enorme Flexibilität, da Motorprimitive wiederverwendet, parametrisiert und auf unterschiedliche Weise kombiniert werden können. Neue Primitive können definiert oder gelernt werden. Ein wichtiger Aspekt dieser Arbeit ist, dass im Gegensatz zu Deep Learning und End-to-End-Lernmethoden, keine umfangreichen Datensätze benötigt werden, um neue Bewegungen zu lernen. Durch die Verwendung von Motorprimitiven kann der gleiche Modellierungsansatz für verschiedene Roboter verwendet werden, indem die Abbildung der Primitive auf die Roboterkinematik neu definiert wird. Die Experimente zeigen, dass durch Motor- primitive die Motorsteuerung für die Manipulation, das Greifen und die Lokomotion vereinfacht werden kann. SNNs für Robotikanwendungen ist immer noch ein Diskussionspunkt. Es gibt keinen State-of-the-Art-Lernalgorithmus, es gibt kein Framework ähnlich dem für Deep Learning, und die Parametrisierung von SNNs ist eine Kunst. Nichtsdestotrotz können Robotikanwendungen - wie Manipulation und Greifen - Benchmarks und realistische Szenarien liefern, um neurowissenschaftliche Modelle zu validieren. Außerdem kann die Robotik die Möglichkeiten der ereignis- basierten Berechnung mit SNNs und neuromorpher Hardware nutzen. Die physikalis- che Nachbildung eines biologischen Systems, das vollständig mit SNNs implementiert und auf echten Robotern evaluiert wurde, kann neue Erkenntnisse darüber liefern, wie der Mensch die Motorsteuerung und Sensorverarbeitung durchführt und wie diese in der Robotik angewendet werden können. Modellfreie Bewegungssteuerungen, inspiriert von den Mechanismen des menschlichen Gehirns, können die Programmierung von Robotern verbessern, indem sie die Steuerung adaptiver und flexibler machen

    THE EFFECTS OF AGING ON MULTIPLE POSTURAL MUSCLE CONTROL AND POSTURAL SWAY BEHAVIOR

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    Episodes of instability and falls in the elderly represent a major public health concern. The lack of scientific information about the effects of age-related changes on neurophysiological mechanisms of postural control has limited the advance in the field of fall prevention and rehabilitation of balance disorders. The overall goal of this dissertation was to investigate the effects of aging on postural control. Considering the progressive non-homogeneous deterioration of aging physiological systems, a series of five experimental studies, with healthy young and healthy nonfaller older adults performing upright stance tasks, explored three main hypotheses: (1) intermuscular coherence analysis is able to detect signs of intermuscular synchronization at lower frequency bands as one of the strategies used by the Central Nervous System to control upright stance; (2) aging is associated with a reorganization of correlated neural inputs controlling postural muscles; and (3) aging is associated with changes in body sway behavior. The first three studies corroborated the use of intermuscular coherence analysis to investigate the formation of correlated neural inputs forming postural muscle synergies during upright stance. The fourth study revealed an age-related reorganization of the distribution and strength of correlated neural inputs to multiple postural muscles. Healthy nonfaller older adults presented stronger levels of synchronization, within 0–10 Hz, for three distinct muscle groups: anterior, posterior, and antagonist muscle groups. The fifth study investigated age-related changes on postural sway using traditional and novel postural indices extracted from the center of pressure coordinates. Although the functional base support is preserved in healthy nonfaller older adults, these seniors revealed a larger, faster, shakier, and more irregular pattern of body sway compared to healthy young adults. In addition, age-related changes on supraspinal mechanisms, spinal reflexes, and intrinsic mechanical properties of muscles and joints involved in postural control were observed by changes in both rambling and trembling components of the postural sway. Findings reported here provide valuable information regarding compensatory mechanisms adopted by healthy nonfaller older adults to control upright stance. Together, these findings suggest an age-related reorganization of correlated neural inputs controlling multiple postural muscles, accompanied by changes in body sway behavior

    On the Role of the Head Ganglia in Posture and Walking in Insects

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    In insects, locomotion is the result of rhythm generating thoracic circuits and their modulation by sensory reflexes and by inputs from the two head ganglia, the cerebral and the gnathal ganglia (GNG), which act as higher order neuronal centers playing different functions in the initiation, goal-direction, and maintenance of movement. Current knowledge on the various roles of major neuropiles of the cerebral ganglia (CRG), such as mushroom bodies (MB) and the central complex (CX), in particular, are discussed as well as the role of the GNG. Thoracic and head ganglia circuitries are connected by ascending and descending neurons. While less is known about the ascending neurons, recent studies in large insects and Drosophila have begun to unravel the identity of descending neurons and their appropriate roles in posture and locomotion. Descending inputs from the head ganglia are most important in initiating and modulating thoracic central pattern generating circuitries to achieve goal directed locomotion. In addition, the review will also deal with some known monoaminergic descending neurons which affect the motor circuits involved in posture and locomotion. In conclusion, we will present a few issues that have, until today, been little explored. For example, how and which descending neurons are selected to engage a specific motor behavior and how feedback from thoracic circuitry modulate the head ganglia circuitries. The review will discuss results from large insects, mainly locusts, crickets, and stick insects but will mostly focus on cockroaches and the fruit fly, Drosophila

    Adapting Highly-Dynamic Compliant Movements to Changing Environments: A Benchmark Comparison of Reflex- vs. CPG-Based Control Strategies

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    To control highly-dynamic compliant motions such as running or hopping, vertebrates rely on reflexes and Central Pattern Generators (CPGs) as core strategies. However, decoding how much each strategy contributes to the control and how they are adjusted under different conditions is still a major challenge. To help solve this question, the present paper provides a comprehensive comparison of reflexes, CPGs and a commonly used combination of the two applied to a biomimetic robot. It leverages recent findings indicating that in mammals both control principles act within a low-dimensional control submanifold. This substantially reduces the search space of parameters and enables the quantifiable comparison of the different control strategies. The chosen metrics are motion stability and energy efficiency, both key aspects for the evolution of the central nervous system. We find that neither for stability nor energy efficiency it is favorable to apply the state-of-the-art approach of a continuously feedback-adapted CPG. In both aspects, a pure reflex is more effective, but the pure CPG allows easy signal alteration when needed. Additionally, the hardware experiments clearly show that the shape of a control signal has a strong influence on energy efficiency, while previous research usually only focused on frequency alignment. Both findings suggest that currently used methods to combine the advantages of reflexes and CPGs can be improved. In future research, possible combinations of the control strategies should be reconsidered, specifically including the modulation of the control signal's shape. For this endeavor, the presented setup provides a valuable benchmark framework to enable the quantitative comparison of different bioinspired control principles

    Does practice of multi-directional stepping with auditory stimulation improve movement performance in patients with Parkinson\u27s disease

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    Parkinson’s disease (PD) is a debilitating neurodegenerative disorder causing many physical limitations. Rhythmic auditory stimulation (RAS) influences motor complications not alleviated by medicine and has been used to modify straight line walking in this population. However, motor complications are exacerbated during more complex movements including those involving direction changes. Thus immediate RAS effects on direction switch duration (DSD) and other kinematic measures during a multi-directional step task were investigated in PD patients. Long term RAS application was also explored by evaluating functional gait and balance and kinematic step measures before and after 6 weeks of multi-directional stepping either with (Cue, C group) or without (No cue, NC group) RAS use. Evaluations were also administered 1, 4 and 8 weeks after training termination. Kinematic measures were collected during stepping without, then with RAS for the C group and without RAS for the NC group. Step testing/training was performed at slow, normal and fast speeds in forward, back and side directions. Participants with PD switched step direction during the stepping task faster with RAS use before training. Like straight line walking RAS application influenced the more complex task of direction switching and counteracted the well-known bradykinesia in PD. After training both groups improved their functional gait and balance measures and maintained balance improvements for at least 8 weeks. Only the C group retained gait improvements for at least 8 weeks after training termination. Adding RAS resulted in functional benefits not observed in training without it. Kinematic measures compared before and after step training clarified the underlying contributors to functional performances. Both groups reduced the variability of DSD. The C group participants maintained this alteration longer. DSD reduction also occurred after training and was retained for at least 8 weeks for this group. These outcomes further support the advantages of adding RAS to training regiments for those with PD. The current results indicate that RAS effects are not limited to simple activities like straight line walking. Moreover, RAS can be used for improving and maintaining improvements longer in activities involving various forms of transition which present most difficulties for those with PD

    Applications of EMG in Clinical and Sports Medicine

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    This second of two volumes on EMG (Electromyography) covers a wide range of clinical applications, as a complement to the methods discussed in volume 1. Topics range from gait and vibration analysis, through posture and falls prevention, to biofeedback in the treatment of neurologic swallowing impairment. The volume includes sections on back care, sports and performance medicine, gynecology/urology and orofacial function. Authors describe the procedures for their experimental studies with detailed and clear illustrations and references to the literature. The limitations of SEMG measures and methods for careful analysis are discussed. This broad compilation of articles discussing the use of EMG in both clinical and research applications demonstrates the utility of the method as a tool in a wide variety of disciplines and clinical fields

    A Bio-inspired architecture for adaptive quadruped locomotion over irregular terrain

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    Tese de doutoramento Programa Doutoral em Engenharia Electrónica e de ComputadoresThis thesis presents a tentative advancement on walking control of small quadruped and humanoid position controlled robots, addressing the problem of walk generation by combining dynamical systems approach to motor control, insights from neuroethology research on vertebrate motor control and computational neuroscience. Legged locomotion is a complex dynamical process, despite the seemingly easy and natural behavior of the constantly present proficiency of legged animals. Research on locomotion and motor control in vertebrate animals from the last decades has brought to the attention of roboticists, the potential of the nature’s solutions to robot applications. Recent knowledge on the organization of complex motor generation and on mechanics and dynamics of locomotion has been successfully exploited to pursue agile robot locomotion. The work presented on this manuscript is part of an effort on the pursuit in devising a general, model free solution, for the generation of robust and adaptable walking behaviors. It strives to devise a practical solution applicable to real robots, such as the Sony’s quadruped AIBO and Robotis’ DARwIn- OP humanoid. The discussed solutions are inspired on the functional description of the vertebrate neural systems, especially on the concept of Central Pattern Generators (CPGs), their structure and organization, components and sensorimotor interactions. They use a dynamical systems approach for the implementation of the controller, especially on the use of nonlinear oscillators and exploitation of their properties. The main topics of this thesis are divided into three parts. The first part concerns quadruped locomotion, extending a previous CPG solution using nonlinear oscillators, and discussing an organization on three hierarchical levels of abstraction, sharing the purpose and knowledge of other works. It proposes a CPG solution which generates the walking motion for the whole-leg, which is then organized in a network for the production of quadrupedal gaits. The devised solution is able to produce goal-oriented locomotion and navigation as directed through highlevel commands from local planning methods. In this part, active balance on a standing quadruped is also addressed, proposing a method based on dynamical systems approach, exploring the integration of parallel postural mechanisms from several sensory modalities. The solutions are all successfully tested on the quadruped AIBO robot. In the second part, is addressed bipedal walking for humanoid robots. A CPG solution for biped walking based on the concept of motion primitives is proposed, loosely based on the idea of synergistic organization of vertebrate motor control. A set of motion primitives is shown to produce the basis of simple biped walking, and generalizable to goal-oriented walking. Using the proposed CPG, the inclusion of feedback mechanisms is investigated, for modulation and adaptation of walking, through phase transition control according to foot load information. The proposed solution is validated on the humanoid DARwIn-OP, and its application is evaluated within a whole-body control framework. The third part sidesteps a little from the other two topics. It discusses the CPG as having an alternative role to direct motor generation in locomotion, serving instead as a processor of sensory information for a feedback based motor generation. In this work a reflex based walking controller is devised for the compliant quadruped Oncilla robot, to serve as purely feedback based walking generation. The capabilities of the reflex network are shown in simulations, followed by a brief discussion on its limitations, and how they could be improved by the inclusion of a CPG.Esta tese apresenta uma tentativa de avanço no controlo de locomoção para pequenos robôs quadrúpedes e bipedes controlados por posição, endereçando o problema de geração motora através da combinação da abordagem de sistemas dinâmicos para o controlo motor, e perspectivas de investigação neuroetologia no controlo motor vertebrado e neurociência computacional. Andar é um processo dinâmico e complexo, apesar de parecer um comportamento fácil e natural devido à presença constante de animais proficientes em locomoção terrestre. Investigação na área da locomoção e controlo motor em animais vertebrados nas últimas decadas, trouxe à atenção dos roboticistas o potencial das soluções encontradas pela natureza aplicadas a aplicações robóticas. Conhecimento recente relativo à geração de comportamentos motores complexos e da mecânica da locomoção tem sido explorada com sucesso na procura de locomoção ágil na robótica. O trabalho apresentado neste documento é parte de um esforço no desenho de uma solução geral, e independente de modelos, para a geração robusta e adaptável de comportamentos locomotores. O foco é desenhar uma solução prática, aplicável a robôs reais, tal como o quadrúpede Sony AIBO e o humanóide DARwIn-OP. As soluções discutidas são inspiradas na descrição funcional do sistema nervoso vertebrado, especialmente no conceito de Central Pattern Generators (CPGs), a sua estrutura e organização, componentes e interacção sensorimotora. Estas soluções são implementadas usando uma abordagem em sistemas dinâmicos, focandos o uso de osciladores não lineares e a explorando as suas propriedades. Os tópicos principais desta tese estão divididos em três partes. A primeira parte explora o tema de locomoção quadrúpede, expandindo soluções prévias de CPGs usando osciladores não lineares, e discutindo uma organização em três níveis de abstracção, partilhando as ideias de outros trabalhos. Propõe uma solução de CPG que gera os movimentos locomotores para uma perna, que é depois organizado numa rede, para a produção de marcha quadrúpede. A solução concebida é capaz de produzir locomoção e navegação, comandada através de comandos de alto nível, produzidos por métodos de planeamento local. Nesta parte também endereçado o problema da manutenção do equilíbrio num robô quadrúpede parado, propondo um método baseado na abordagem em sistemas dinâmicos, explorando a integração de mecanismos posturais em paralelo, provenientes de várias modalidades sensoriais. As soluções são todas testadas com sucesso no robô quadrupede AIBO. Na segunda parte é endereçado o problema de locomoção bípede. É proposto um CPG baseado no conceito de motion primitives, baseadas na ideia de uma organização sinergética do controlo motor vertebrado. Um conjunto de motion primitives é usado para produzir a base de uma locomoção bípede simples e generalizável para navegação. Esta proposta de CPG é usada para de seguida se investigar a inclusão de mecanismos de feedback para modulação e adaptação da marcha, através do controlo de transições entre fases, de acordo com a informação de carga dos pés. A solução proposta é validada no robô humanóide DARwIn-OP, e a sua aplicação no contexto do framework de whole-body control é também avaliada. A terceira parte desvia um pouco dos outros dois tópicos. Discute o CPG como tendo um papel alternativo ao controlo motor directo, servindo em vez como um processador de informação sensorial para um mecanismo de locomoção puramente em feedback. Neste trabalho é desenhado um controlador baseado em reflexos para a geração da marcha de um quadrúpede compliant. As suas capacidades são demonstradas em simulação, seguidas por uma breve discussão nas suas limitações, e como estas podem ser ultrapassadas pela inclusão de um CPG.The presented work was possible thanks to the support by the Portuguese Science and Technology Foundation through the PhD grant SFRH/BD/62047/2009
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