Design Principles for FES Concept Development

© Cranfield University 2013. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright owner.A variety of pathologies can cause injury to the spinal cord and hinder movement. A range of equipment is available to help spinal injury sufferers move their affected limbs. One method of rehabilitation is functional electrical stimulation (FES). FES is a technique where small electrical currents are applied to the surface of the user’s legs to stimulate the muscles. Studies have demonstrated the benefits of using this method and it has also been incorporated into a number of devices. The aim of the project was to produce a number of designs for a new device that uses FES technology. The project was completed in conjunction with an industrial partner. A review of the literature and consultation with industrial experts suggested a number of ways current devices could be improved. These included encouraging the user to lean forwards while walking and powering the device using a more ergonomic method. A group of designers were used to produce designs that allowed the user to walk with a more natural gait and avoided cumbersome power packs. The most effective of these designs were combined to form one design that solved both problems. A 3-dimensional model of this design was simulated using computer-aided design software. Groups of engineers, scientists and consumers were also invited to provide input on how a new device should function. Each of these groups provided a design that reflected their specific needs, depending on their experience with similar technology. Low level prototypes were produced of these designs. A group of designers were also used to design concepts for a functional electrical stimulation device based on an introduction given by industry experts. Each of the designs was presented to experienced professionals to obtain feedback. A set of guidelines were also produced during the project that instructed how to create the designs

Optimal workloop energetics of muscle-actuated systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2007.Includes bibliographical references (p. 117-122).Skeletal muscles are the primary actuators that power, stabilize and control locomotive and functional motor tasks in biological systems. It is well known that coordinated action and co-activation of multiple muscles give rise to desirable effects such as enhanced postural and dynamic stability. In this thesis, we study the role of muscle co-activation from an energetics perspective: Are there situations in which antagonist co-activation leads to enhanced power generation, and if so, what is the underlying mechanism? The mechanical energetics of muscles are traditionally characterized in terms of workloop measures where muscles are activated against oscillating, zero-admittance motion sources. We extend these measures to more natural, "mid-range" admittance loads, actuated by multiple muscles. Specifically, we set up the problem of a second-order mechanical system driven by a pair of antagonist muscles. This is the simplest problem where the influences of load dynamics and muscle co-activation on the output energetics may be investigated. To enable experimentation, a muscle testing apparatus capable of real-time servo emulation of the load is developed and utilized for identification and workloop measurements.(cont.) Using this apparatus, an experimentally identified model predicting muscle contractile force is proposed. Experimental data shows that with a simple Weiner structure, the model accounts for 74% (sigma = 5.6%) of the variance in muscle force, that force dependence on contraction velocity is minimal, and that a bilinear approximation of the output nonlinearity is warranted. Based on this model we investigate what electrical stimulation input gives rise to maximal power transfer for a particular load. This question is cast in an optimal control framework. Necessary conditions for optimality are derived and methods for computing solutions are presented. Solutions demonstrate that the optimal stimulation frequencies must include the effects of muscle impedances, and that optimal co-activation levels are indeed modulated to enable a pair of muscles to produce more work synergistically rather than individually. Pilot experimental data supporting these notions is presented. Finally, we interpret these results in the context of the familiar engineering notion of impedance matching. These results shed new light on the role of antagonist co-activation from an energetics perspective.by Walled A. Farahat.Ph.D

A Bilateral Training System for Upper-limb Rehabilitation: A Follow-up Study

Previously, we reported a novel bilateral upper-limb rehabilitation system, an adaptive admittance controller and a related bilateral recovery strategy. In this study, we want to get a stronger evidence to verify the robustness of the proposed system, controller and recovery strategy as well as to further investigate the possibility of bilateral trainings for clinical applications. To this end, ten healthy subjects took part in a 60-minute experiment. Trajectories of robots and interaction force were recorded under the proposed bilateral recovery strategy which contained four exercise modes. For mode-l and mode-2, results showed that the trajectories of master and slave robots can catch the reference trajectory very well, and be changed with active interaction force applied by participants. For mode-3 and mode-4, participants finished tasks very well by drawing the ‘square-shaped’ trajectories through their own force. In conclusion, the experimental results were good enough to provide a strong and positive evidence for the proposed system and controller. Moreover, according to the feedbacks from participants, the bilateral recovery strategy can be treated as a new and interesting training as compared to the traditional unilateral training, and could be tested in clinical applications further

Adaptive control for wearable robots in human-centered rehabilitation tasks

Robotic rehabilitation therapies have been improving by providing the needed assistance to the patient, in a human-centered environment, and also helping the therapist to choose the necessary procedure. This thesis presents an adaptive "Assistance-as-needed" strategy which adheres to the specific needs of the patient and with the inputs from the therapist, whenever needed. The exertion of assistive and responsive behavior of the lower limb wearable robot is dedicated for the rehabilitation of incomplete spinal cord injury (SCI) patients. The main objective is to propose and evaluate an adaptive control model on a wearable robot, assisting the user and adhering to their needs, with no or less combination of external devices. The adaptation must be more interactive to understand the user needs and their volitional orders. Similarly, by using the existing muscular strength, in incomplete SCI patients, as a motivation to pursue the movement and assist them, only when needed. The adaptive behavior of the wearable robot is proposed by monitoring the interaction and movement of the user. This adaptation is achieved by modulating the stiffness of the exoskeleton in function of joint parameters, such as positions and interaction torques. These joint parameters are measured from the user independently and then used to update the new stiffness value. The adaptive algorithm performs with no need of external sensors, making it simple in terms of usage. In terms of rehabilitation, it is also desirable to be compatible with combination of assistive devices such as muscle stimulation, neural activity (BMI) and body balance (Wii), to deliver a user friendly and effective therapy. Combination of two control approaches has been employed, to improve the efficiency of the adaptive control model and was evaluated using a wearable lower limb exoskeleton device, H1. The control approaches, Hierarchical and Task based approach have been used to assist the patient as needed and simultaneously motivate the patient to pursue the therapy. Hierarchical approach facilitates combination of multiple devices to deliver an effective therapy by categorizing the control architecture in two layers, Low level and High level control. Task-based approaches engage in each task individually and allow the possibility to combine them at any point of time. It is also necessary to provide an interaction based approach to ensure the complete involvement of the user and for an effective therapy. By means of this dissertation, a task based adaptive control is proposed, in function of human-orthosis interaction, which is applied on a hierarchical control scheme. This control scheme is employed in a wearable robot, with the intention to be applied or accommodated to different pathologies, with its adaptive capabilities. The adaptive control model for gait assistance provides a comprehensive solution through a single implementation: Adaptation inside a gait cycle, continuous support through gait training and in real time. The performance of this control model has been evaluated with healthy subjects, as a preliminary study, and with paraplegic patients. Results of the healthy subjects showed a significant change in the pattern of the interaction torques, elucidating a change in the effort and adaptation to the user movement. In case of patients, the adaptation showed a significant improvement in the joint performance (flexion/extension range) and change in interaction torques. The change in interaction torques (positive to negative) reflects the active participation of the patient, which also explained the adaptive performance. The patients also reported that the movement of the exoskeleton is flexible and the walking patterns were similar to their own distinct patterns. The presented work is performed as part of the project HYPER, funded by Ministerio de Ciencia y Innovación, Spain. (CSD2009 - 00067 CONSOLIDER INGENIOLas terapias de rehabilitación robóticas han sido mejoradas gracias a la inclusión de la asistencia bajo demanda, adaptada a las variaciones de las necesidades del paciente, así como a la inclusión de la ayuda al terapeuta en la elección del procedimiento necesario. Esta tesis presenta una estrategia adaptativa de asistencia bajo demanda, la cual se ajusta a las necesidades específicas del paciente junto a las aportaciones del terapeuta siempre que sea necesario. El esfuerzo del comportamiento asistencial y receptivo del robot personal portátil para extremidades inferiores está dedicado a la rehabilitación de pacientes con lesión de la médula espinal (LME) incompleta. El objetivo principal es proponer y evaluar un modelo de control adaptativo en un robot portátil, ayudando al usuario y cumpliendo con sus necesidades, en ausencia o con reducción de dispositivos externos. La adaptación debe ser más interactiva para entender las necesidades del usuario y sus intenciones u órdenes volitivas. De modo similar, usando la fuerza muscular existente (en pacientes con LME incompleta) como motivación para lograr el movimiento y asistirles solo cuando sea necesario. El comportamiento adaptativo del robot portátil se propone mediante la monitorización de la interacción y movimiento del usuario. Esta adaptación conjunta se consigue modulando la rigidez en función de los parámetros de la articulación, tales como posiciones y pares de torsión. Dichos parámetros se miden del usuario de forma independiente y posteriormente se usan para actualizar el nuevo valor de la rigidez. El desempeño del algoritmo adaptativo no requiere de sensores externos, lo que favorece la simplicidad de su uso. Para una adecuada rehabilitación, efectiva y accesible para el usuario, es necesaria la compatibilidad con diversos mecanismos de asistencia tales como estimulación muscular, actividad neuronal y equilibrio corporal. Para mejorar la eficiencia del modelo de control adaptativo se ha empleado una combinación de dos enfoques de control, y para su evaluación se ha utilizado un exoesqueleto robótico H1. Los enfoques de control Jerárquico y de Tarea se han utilizado para ayudar al usuario según sea necesario, y al mismo tiempo motivarle para continuar el tratamiento. Enfoque jerárquico facilita la combinación de múltiples dispositivos para ofrecer un tratamiento eficaz mediante la categorización de la arquitectura de control en dos niveles : el control de bajo nivel y de alto nivel. Los enfoques basados en tareas involucran a la persona en cada tarea individual, y ofrecen la posibilidad de combinarlas en cualquier momento. También es necesario proporcionar un enfoque basado en la interacción con el usuario, para asegurar su participación y lograr así una terapia eficaz. Mediante esta tesis, proponemos un control adaptativo basado en tareas y en función de la interacción persona-ortesis, que se aplica en un esquema de control jerárquico. Este esquema de control se emplea en un robot portátil, con la intención de ser aplicado o acomodado a diferentes patologías, con sus capacidades de adaptación. El modelo de control adaptativo propuesto proporciona una solución integral a través de una única aplicación: adaptación dentro de la marcha y apoyo continúo a través de ejercicios de movilidad en tiempo real. El rendimiento del modelo se ha evaluado en sujetos sanos según un estudio preliminar, y posteriormente también en pacientes parapléjicos. Los resultados en sujetos sanos mostraron un cambio significativo en el patrón de los pares de interacción, elucidando un cambio en la energía y la adaptación al movimiento del usuario. En el caso de los pacientes, la adaptación mostró una mejora significativa en la actuación conjunta (rango de flexión / extensión) y el cambio en pares de interacción. El cambio activo en pares de interacción (positivo a negativo) refleja la participación activa del paciente, lo que también explica el comportamiento adaptativo

Pathological Tremor as a Mechanical System: Modeling and Control of Artificial Muscle-Based Tremor Suppression

Central nervous system disorders produce the undesired, approximately rhythmic movement of body parts known as pathological tremor. This undesired motion inhibits the patient\u27s ability to perform tasks of daily living and participate in society. Typical treatments are medications and deep brain stimulation surgery, both of which include risks, side effects, and varying efficacy. Since the pathophysiology of tremor is not well understood, empirical investigation drives tremor treatment development. This dissertation explores tremor from a mechanical systems perspective to work towards theory-driven treatment design. The primary negative outcome of pathological tremor is the undesired movement of body parts: mechanically suppressing this motion provides effective tremor treatment by restoring limb function. Unlike typical treatments, the mechanisms for mechanical tremor suppression are well understood: applying joint torques that oppose tremor-producing muscular torques will reduce tremor irrespective of central nervous system pathophysiology. However, a tremor suppression system must also consider voluntary movements. For example, mechanically constraining the arm in a rigid cast eliminates tremor motion, but also eliminates the ability to produce voluntary motions. Indeed, passive mechanical systems typically reduce tremor and voluntary motions equally due to the close proximity of their frequency content. Thus, mechanical tremor suppression requires active actuation to reduce tremor with minimal influence on voluntary motion. However, typical engineering actuators are rigid and bulky, preventing clinical implementations. This dissertation explores dielectric elastomers as tremor suppression actuators to improve clinical implementation potential of mechanical tremor suppression. Dielectric elastomers are often called artificial muscles due to their similar mechanical properties as human muscle; these similarities may enable relatively soft, low-profile implementations. The primary drawback of dielectric elastomers is their relatively low actuation levels compared to typical actuators. This research develops a tremor-active approach to dielectric elastomer-based tremor suppression. In a tremor-active approach, the actuators only actuate to oppose tremor, while the human motor system must overcome the passive actuator dynamics. This approach leverages the low mechanical impedance of dielectric elastomers to overcome their low actuation levels. Simulations with recorded tremor datasets demonstrate excellent and robust tremor suppression performance. Benchtop experiments validate the control approach on a scaled system. Since dielectric elastomers are not yet commercially available, this research quantifies the necessary dielectric elastomer parameters to enable clinical implementations and evaluates the potential of manufacturing approaches in the literature to achieve these parameters. Overall, tremor-active control using dielectric elastomers represents a promising alternative to medications and surgery. Such a system may achieve comparable tremor reduction as medications and deep brain stimulation with minimal risks and greater efficacy, but at the cost of increased patient effort to produce voluntary motions. Parallel advances in scaled dielectric elastomer manufacturing processes and high-voltage power electronics will enable consumer implementations. In addition to tremor suppression, this dissertation investigates the mechanisms of central nervous system tremor generation from a control systems perspective. This research investigates a delay-based model for parkinsonian tremor. Besides tremor, Parkinson\u27s disease generally inhibits movement, with typical symptoms including rigidity, bradykinesia, and increased reaction times. This fact raises the question as to how the same disease produces excessive movement (tremor) despite characteristically inhibiting movement. One possible answer is that excessive central nervous system inhibition produces unaccounted feedback delays that cause instability. This dissertation develops an optimal control model of human motor control with an unaccounted delay between the state estimator and controller. This delay represents the increased inhibition projected from the basal ganglia to the thalamus, delaying signals traveling from the cerebellum (estimator) to the primary motor cortex (controller). Model simulations show increased delays decrease tremor frequency and increase tremor amplitude, consistent with the evolution of tremor as the disease progresses. Simulations that incorporate tremor resetting and random variation in control saturation produce simulated tremor with similar characteristics as recorded tremor. Delay-induced tremor explains the effectiveness of deep brain stimulation in both the thalamus and basal ganglia since both regions contribute to the presence of feedback delay. Clinical evaluation of mechanical tremor suppression may provide clinical evidence for delay-induced tremor: unlike state-independent tremor, suppression of delay-induced tremor increases tremor frequency. Altogether, establishing the mechanisms for tremor generation will facilitate pathways towards improved treatments and cure development

An ultra low power implantable neural recording system for brain-machine interfaces

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 179-187).In the past few decades, direct recordings from different areas of the brain have enabled scientists to gradually understand and unlock the secrets of neural coding. This scientific advancement has shown great promise for successful development of practical brain-machine interfaces (BMIs) to restore lost body functions to patients with disorders in the central nervous system. Practical BMIs require the uses of implantable wireless neural recording systems to record and process neural signals, before transmitting neural information wirelessly to an external device, while avoiding the risk of infection due to through-skin connections. The implantability requirement poses major constraints on the size and total power consumption of the neural recording system. This thesis presents the design of an ultra-low-power implantable wireless neural recording system for use in brain-machine interfaces. The system is capable of amplifying and digitizing neural signals from 32 recording electrodes, and processing the digitized neural data before transmitting the neural information wirelessly to a receiver at a data rate of 2.5 Mbps. By combining state-of-the-art custom ASICs, a commercially-available FPGA, and discrete components, the system achieves excellent energy efficiency, while still offering design flexibility during the system development phase. The system's power consumption of 6.4 mW from a 3.6-V supply at a wireless output data rate of 2.5 Mbps makes it the most energy-efficient implantable wireless neural recording system reported to date. The system is integrated on a flexible PCB platform with dimensions of 1.8 cm x 5.6 cm and is designed to be powered by an implantable Li-ion battery. As part of this thesis, I describe the design of low-power integrated circuits (ICs) for amplification and digitization of the neural signals, including a neural amplifier and a 32-channel neural recording IC. Low-power low-noise design techniques are utilized in the design of the neural amplifier such that it achieves a noise efficiency factor (NEF) of 2.67, which is close to the theoretical limit determined by physics. The neural recording IC consists of neural amplifiers, analog multiplexers, ADCs, serial programming interfaces, and a digital processing unit. It can amplify and digitize neural signals from 32 recording electrodes, with a sampling rate of 31.25 kS/s per channel, and send the digitized data off-chip for further processing. The IC was successfully tested in an in-vivo wireless recording experiment from a behaving primate with an average power dissipation per channel of 10.1 [mu]W. Such a system is also widely useful in implantable brain-machine interfaces for the blind and paralyzed, and in cochlea implants for the deaf.by Woradorn Wattanapanitch.Ph.D

DICOM for EIT

With EIT starting to be used in routine clinical practice [1], it important that the clinically relevant information is portable between hospital data management systems. DICOM formats are widely used clinically and cover many imaging modalities, though not specifically EIT. We describe how existing DICOM specifications, can be repurposed as an interim solution, and basis from which a consensus EIT DICOM ‘Supplement’ (an extension to the standard) can be writte

Effects of dance therapy on balance, gait and neuro-psychological performances in patients with Parkinson's disease and postural instability

Postural Instability (PI) is a core feature of Parkinson’s Disease (PD) and a major cause of falls and disabilities. Impairment of executive functions has been called as an aggravating factor on motor performances. Dance therapy has been shown effective for improving gait and has been suggested as an alternative rehabilitative method. To evaluate gait performance, spatial-temporal (S-T) gait parameters and cognitive performances in a cohort of patients with PD and PI modifications in balance after a cycle of dance therapy