Switching Adaptive Concurrent Learning Control for Powered Rehabilitation Machines with FES

Interfacing robotic devices with humans presents significant control challenges, as the control algorithms governing these machines must accommodate for the inherent variability among individuals. This requirement necessitates the system’s ability to adapt to changes in the environment, particularly in the context of human-in-the-loop applications, wherein the system must identify specific features of the human interacting with the machine. In the field of rehabilitation, one promising approach for exercise-based rehabilitation involves the integration of hybrid rehabilitation machines, combining robotic devices such as motorized bikes and exoskeletons with functional electrical stimulation (FES) applied on lower-limb muscles. This integrated approach offers the potential for repetitive training, reduced therapist workload, improved range of motion, and therapeutic benefits. However, conducting prolonged rehabilitation sessions to maximize functional recovery using these hybrid machines imposes several difficulties. Firstly, the design and analysis of adaptive controllers are motivated, but challenges exist in coping with the inherent switching effects associated with hybrid machines. Notably, the transitions between gait phases and the dynamic switching of inputs between active lower-limb muscles and electric motors and their incorporation in the control design remain an open problem for the research community. Secondly, the system must effectively compensate for the influence of human input, which can be viewed as an external disturbance in the closed-loop system during rehabilitation. Robust methods for understanding and adapting to the variations in human input are critical for ensuring stability and accurate control of the human-robot closed-loop system. Lastly, FES-induced muscle fatigue diminishes the human torque contribution to the rehabilitation task, leading to input saturation and potential instabilities as the duration of the exercise extends. Overcoming this challenge requires the development of control algorithms that can adapt to variations in human performance by dynamically adjusting the control parameters accordingly. Consequently, the development of rehabilitative devices that effectively interface with humans requires the design and implementation of control algorithms capable of adapting to users with varying muscle and kinematic characteristics. In this regard, adaptive-based control methods provide tools for addressing the uncertainties in human-robot dynamics within exercise-based rehabilitation using FES, while ensuring stability and robustness in the human-robot closed-loop system. This dissertation develops adaptive controllers to enhance the effectiveness of exercise-based rehabilitation using FES. The objectives include the design and evaluation of adaptive control algorithms that effectively handle the switching effects inherent in hybrid machines, adapt to compensate for human input, and account for input saturation due to muscle fatigue. The control designs leverage kinematic and torque feedback and ensure the stability of the human-robot closed-loop system. These controllers have the potential to significantly enhance the practicality and effectiveness of assistive technologies in both clinical and community settings. In Chapter 1, the motivation to design switching adaptive closed-loop controllers for motorized FES-cycling and powered exoskeletons is described. A survey of closed-loop kinematic control methods related to the tracking objectives in the subsequent chapters of the dissertation is also introduced. In Chapter 2, the dynamic models for cycling and bipedal walking are described: (i) a stationary FES-cycling model with nonlinear dynamics and switched control inputs are introduced based on published literature. The muscle stimulation pattern is defined based on the kinematic effectiveness of the rider, which depends on the crank angle. (ii) A phase-dependent bipedal walking system model with switched dynamics is introduced to control a 4-degrees-of-freedom (DoF) lower-limb exoskeleton assuming single stance support. Moreover, the experimental setup of the cycle-rider and lower-limb exoskeleton system are described. Chapter 3 presents a switched concurrent learning adaptive controller for cadence tracking using the cycle-rider model. The control design is decoupled for the muscles and electric motor. An FES controller is developed with minimal parameters, capable of generating bounded muscle responses with an adjustable saturation limit. The electric motor controller employs an adaptive-based method that estimates uncertain parameters in the cycle-rider system and leverages the muscle input as a feedforward term to improve the tracking of crank trajectories. The adaptive motor controller and saturated muscle controller are implemented in able-bodied individuals and people with movement disorders. Three cycling trials were conducted to demonstrate the feasibility of tracking different crank trajectories with the same set of control parameters across all participants. The developed adaptive controller requires minimal tuning and handles rider uncertainty while ensuring predictable and satisfactory performance. This result has the potential to facilitate the widespread implementation of adaptive closed-loop controllers for FES-cycling systems in real clinical and home-based scenarios. Chapter 4 presents an integral torque tracking controller with anti-windup compensation, which achieves the dual objectives of kinematic and torque tracking (i.e., power tracking) for FES cycling. Designing an integral torque tracking controller to avoid feedback of high-order derivatives poses a significant challenge, as the integration action in the muscle loop can induce error buildup; demanding high FES input on the muscle. This can cause discomfort and accelerate muscle fatigue, thereby limiting the practical utility of the power tracking controller. To address this issue, this chapter builds upon the adaptive control for cadence tracking developed in Chapter 3 and integrates a novel torque tracking controller that allows for input saturation in the FES controller. By doing so, the controller achieves cadence and torque tracking while preventing error buildup. The analysis rigorously considers the saturation effect, and preliminary experimental results in able-bodied individuals demonstrate its feasibility. In Chapter 5, a switched concurrent learning adaptive controller is developed to achieve kinematic tracking throughout the step cycle for treadmill-based walking with a 4-DoF lower-limb hybrid exoskeleton. The developed controller leverages a phase-dependent human-exoskeleton model presented in Chapter 2. A multiple-Lyapunov stability analysis with a dwell time condition is developed to ensure exponential kinematic tracking and parameter estimation. The controller is tested in two able-bodied individuals for a six-minute walking trial and the performance of the controller is compared with a gradient descent classical adaptive controller. Chapter 6 highlights the contributions of the developed control methods and provides recommendations for future research directions

A hand exoskeleton for study of rehabilitation and assistance of spinal cord injury patients

A large number of people experience neurological disorders in their life time, and these patients seek to regain their body functions with rehabilitation and assistive devices. In this dissertation, we present the development of a hand exoskeleton, called Maestro, which is designed to advance research in fields of hand rehabilitation and hand assistive devices. Maestro is mechanically and electrically robust, accurate in sensing and actuation, and compatible to various rehabilitation schemes, subjects, hardware/software, and different operators. As a result of these features, Maestro has led to research on adaptive control theories for diverse properties of hands, the development of a hand-wrist exoskeleton, the development of a novel rehabilitation framework, progress of hand muscle fatigues, and assistance for SCI patients. Particularly on the assistance for SCI patients, we present that the advantage of a compliant hand assistive device may result in high success ratios for grasping various objects required in activities of daily living (ADL) with surface EMG sensors. The hand functions of SCI subjects are evaluated with and without Maestro through a standardized hand function test called Sollerman hand function test (SHFT). The results with six SCI subjects show that the hand functions of C6 and C7 SCI subjects improved with assistance from Maestro.Mechanical Engineerin

Bio-inspired Mechatronic Design for the Actuation of a Soft Orthosis for Rehabilitation and Assistance of Hands

Proyecto de Graduación (Licenciatura en Ingeniería en Mecatrónica) Instituto Tecnológico de Costa Rica. Escuela de Ingeniería en Mecatrónica, 2010.It is described the design of a mechatronic system to actuate a hand soft orthotic device for rehabilitation and assistance purposes developed by the author of this thesis within the Bio Mechatronics Department of Fraunhofer Institute for Manufacturing Engineering and Automation (IPA) based in Stuttgart, Germany. The system mimics the musculoskeletal anatomy and kinesiology of the human body by resembling the bone-muscle-tendon configuration. A key feature of the orthosis is that allows the individual movement of the fingers. The actuation consists in the use of -high contraction- Festo Pneumatic Artificial Muscles (PAMs) within a 3D printed support structure which was designed using anthropometric data to aim to comfort and ergonomics. The PAMs are operated with piezoelectric -flow proportional- valves. The sensors mimic the human somatosensory system to control the motion and to confer a haptic nature to the human interface. The use of light indicators allows visual reinforcement during exercises. The final deliverable is a testing model that is going to be used for further experiments. Finally, this orthotic device is envisioned to become a mobile solution for self-aided rehabilitation.Instituto Tecnológico de Costa Rica. Escuela de Ingeniería en Mecatrónica. Fraunhofer Institute for Manufacturing Engineering and Automation (Fraunhofer IPA)

Adaptive shared-control of a robotic walker to improve human-robot cooperation in gait biomechanical rehabilitation

Dissertação de mestrado integrado em Engenharia Biomédica (especialização em Eletrónica Médica)Sessões de reabilitação de pacientes com deficiências na marcha é importante para que a qualidade de vida dos mesmos seja recuperada. Quando auxiliadas por andarilhos robóticos inteligentes as sessões têm mostrado melhorias significativas, face aos resultados obtidos por métodos clássicos. O andarilho WALKit é um dos dispositivos mencionados e permite ser conduzido por parte do paciente enquanto um especialista supervisiona todo o processo de forma a evitar colisões e quedas. Este processo de supervisão é moroso e requer constante presença de um especialista para cada paciente. Nesta dissertação é proposto um controlador autónomo e inteligente capaz de partilhar a condução do andarilho pelo paciente e pelo supervisor evitando colisões com obstáculos. Para remover a necessidade constante do médico supervisor, um módulo de condução autónoma foi desenvolvido. O modo autónomo proposto usa um sensor Light Detection and Ranging e o algoritmo de Simultaneous Localization and Mapping (Cartographer) para obter mapas e a localização do andarilho. Seguidamente, os planeadores global e local , A* e Dynamic Window Approach respetivamente, traçam caminhos válidos para o destino, interpretáveis pelo andarilho. Usando o modo autónomo como especialista e as intenções do paciente, o controlador partilhado usa o algoritmo Proximal Policy Optimization, aprendendo o comportamento pretendido através de um processo de tentiva e erro, maximizando a recompensa recebida através de uma função pré-estabelecida. Uma rede neuronal com camadas convolucionais e lineares é capaz de inferir o risco enfrentado pelo sistema paciente-WALKit e determinar se o modo autónomo deve assumir controlo de forma a neutralizar o risco mencionado. Globalmente foram detetados erros inferiores a 38 cm no sistema de mapeamento e localização. Quer nos cenários de testagem do controlador autónomo, quer nos do controlador partilhado, nenhuma colisão foi registada garantindo em todas as tentativas a chegada ao destino escolhido. O modo autónomo, apesar de evitar obstáculos, não foi capaz de alcançar certos destinos não contemplados em ambientes de reabilitação. O modo partilhado mostrou também certas transições bruscas entre modo autónomo e intenção que podem comprometer a segurança do paciente. É necessário, como trabalho futuro, estabelecer métricas de validação objetivas e testar o controlador com pacientes de forma a corretamente estimar o desempenho.Rehabilitation sessions of patients with gait disabilities is important to restore quality of life. When aided by intelligent robotic walkers the sessions have shown significant improvements when compared to the results obtained by classical methods. The WALKit walker is one of the devices mentioned and allows the patient to drive it while a medical expert supervises the entire process in order to avoid collisions and falls. This supervision process takes time and requires constant presence of a medical expert for each patient. This dissertation proposes an intelligent controller capable of sharing the walker’s drivability by the patient and the supervisor, avoiding collisions with obstacles. To remove the constant need of a supervisor, an autonomous driving module was developed. The proposed autonomous mode uses a Light Detection and Ranging sensor and the Simultaneous Localization and Mapping (Cartographer ) algorithm to obtain maps and the location of the walker. Then, the global and local planners, A * and Dynamic Window Approach respectively, draw valid paths to the destination, interpretable by the walker. Using the autonomous mode as a expert and the patient’s intentions, the SC uses the Proximal Policy Optimization algorithm, learning the intended behavior through a trial and error process, maximizing the reward received through a pre-established function. One neural network with convolutional and linear layers is able to infer the risk faced by the patient-WALKit system and determine whether the autonomous mode should take control in order to neutralize the mentioned risk. Globally, errors smaller than 38 cm were detected in the mapping and localization system. In the testing scenarios of the autonomous controller and in the SC no collisions were recorded guaranteeing the arrival at the chosen destination in all attempts. The autonomous mode, despite avoiding obstacles, was not able to reach certain destinations not covered in rehabilitation environments. The shared mode has also shown certain sudden transitions between autonomous mode and intention that could compromise patient safety. It is necessary, as future work, to establish objective validation metrics and testing the controller with patients is necessary in order to correctly estimate performance

Modèles d’intégration des designers créatifs dans les processus de conception industriels

Many studies show that industrial design is key to triggering, fostering andsustaining innovation. However, the unique capacities of creation and innovationof industrial designers make it challenging for them to thrive within industrialenvironments.The challenge for companies is to create the optimal work environment forthose professionals, while ensuring their work can be integrated smoothly intothe existing industrial design processes. We assume this dilemma is partiallystemming from the intensive use of sequential design models in the industry.Design tools were developed on the assumption that creative front end andproduct development should be separated.We introduce here a new model, aiming at depicting accurately the reasoningmodes and the nature of the object being designed with the digital ComputerAided Design (CAD) suites. This model is the result of the joint mobilization offour academic fields : computer, cognitive and management science and designtheories. Dassault Systèmes and their CATIA software have proven to be an excellentresearch environment for such questions. As we have been thinking, thenew model (laminated) makes three new hypothesis. Those unheard assertionshave been suggested and validated with this thesis :1/ Some specific design workshops are able to provide simultaneously robust andgenerative design capacities. We call this characteristic «acquired originality».2/ The object representations within by the software are not the result of successiverefinements but derive directly from a parameterized set of rules.3/ Industrial designers have specific requirements for CAD tools, different fromtheir engineers and artists counterparts because what they design is fundamentallydifferent. IDs generate conceptual models using a mass singularity technique.Those results sketch the emergence of a new generation of CAD tools forindustrial designers and able to foster innovation.De décisifs et puissants enjeux d'innovation ainsi que de renouvellement del'identité des objets bouleversent le monde industriel. De telles aptitudes créativessont usuellement associées aux designers industriels. Cependant, ces professionnelsne sont actuellement pas intégrés dans les processus numériques deconception.Afin de décrire ce paradoxe, nous formulons l'hypothèse que, l'omniprésencedans l'industrie de modèles de la conception de type séquentiel, qui juxtaposentcréativité et développement produit, entrave l'intégration des designers industrielsau sein des processus industriels. En effet, en compartimentant la conceptionen silos, ce type de modèles généralistes inhibe les méthodes spécifiquesdes concepteurs créatifs. Bien plus, les outils numériques adjoints au modèle séquentielétant calqués sur sa logique, ils reproduisent et les inconvénients d'unetelle structuration.En mobilisant quatre disciplines académiques qui traitent des outils numériques,à savoir les sciences informatiques, cognitives, de gestion et les théoriesde la conception, nous élaborons un nouveau modèle «dit stratifié». Ce dernierrévèle les modes de raisonnement empruntés par les concepteurs créatifs ainsique la nature des produits élaborés dans les environnements logiciels. A ce titre,l'entreprise Dassault Systèmes ainsi que la suite CATIA se sont révélés un substratde recherche idéal. Comme attendu, notre nouveau modèle propose desassertions inédites qui sont validées au cours de notre travail. Nous avons alorsdémontré que :1/ Certains ateliers de conception favorisent simultanément robustesse et générativité.Nous qualifions cette nouvelle propriété d'«originalité acquise».2/ Les avatars dans le logiciel ne résultent pas d'un raffinement progressif del'objet mais sont plutôt l'instanciation d'une base de règles paramétrée.3/ Les designers industriels requièrent des outils distincts de ceux employés parles artistes 3D ou les ingénieurs, de par la nature de leur conception. Plus exactement,ces professionnels génèrent des modèles conceptuels selon une logiquede singularité de masse.Ces résultats offrent ainsi la perspective engageante de l'émergence d'unenouvelle génération d'outils numériques de conception. Ces outils inédits serontaptes à intégrer les designers industriels et à proposer de l'innovation à la d