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Members of the elderly population is disproportionately prone to experiencing mobility impairment due to their aging bodies and as a result have frail bodies that are at a higher risk of grave injury due to falling. In order to combat this assistive mobility devices such as exoskeletons have been developed to help patients enhance their range of motion. With additive manufacturing techniques, such as fused deposition modeling (FDM), becoming a more mainstream form of design, the inclusion of lightweight polymers such as nylon 12 as primary construction materials for these devices has increased. In this thesis computer aided design (CAD) software was used to design a prototype lower body exoskeleton and simulation software was used to give the device the characteristics of Stratasys' nylon 12 carbon fiber FDM material to verify it if could be used as the primary construction material for this device when extruded from a FDM printer on either the XZ or ZX printing plane. From the simulations it was found that the material printed along the XZ plane could create a device that could withstand the weight of an average elderly male patient (200 lbs.) as well as the 35 lbs. of force applied to the device by a linear actuation motor that would be used to extend and contract the exoskeleton leg.

The musculoskeletal disorders have significant health care, social and economic consequences in the factories nowadays. One of the most promising possible solutions is the use of exoskeletons in the workstations. Exoskeletons are assistive wearable robotics connected to the body of a person, which aims to give mechanical power or mobility to the user (Wang, Ikuma, Hondzinski, & de Queiroz, 2017). The objective of this project is to create a realistic CAD model of a passive exoskeleton which will be used in future research to analyse the behaviour of the workers in a virtual environment with and without the exoskeleton. This model will be a virtual representation of the exoskeleton EKSOVest which has been designed to support these workers who have to realize overhead tasks. This virtual representation will be carried out in PTC CREO and exported to IPS IMMA in order to check the viability of this model. To achieve a realistic model, the exoskeleton should have the same characteristics than the real exoskeleton. The objectives of this project will be defined for these characteristics, which are part creation, mechanisms, forces simulation, and parametrization. The parts and the mechanisms will be created and defined in PTC CREO with the same dimensions and behaviour as the real exoskeleton. Furthermore, this report will be focussed mainly in force simulation and the parametrization. The forces of the EKSOVest are generated by two different spring and by a high-pressure spring. To simulate these forces, the equation of these springs will be obtained and introduced in PTC CREO. These equations will be obtained through the regression of a set of points, which will be obtained from the real exoskeleton using a dynamometer. The parametrization will be carried out with the objective to make the virtual model adaptable for every type of mannequins. This parametrization will modify the length of the exoskeleton’s spine bar and the distance between the mechanical arms. These distances will be adapted according to the mannequin’s measures which will be introduced by the user. The measures that have to be introduced by the user are shoulder height, liac spine height, and chest width. In conclusion, it can be said that the regression of the springs obtained are an accurate result which can imitate quite well the forces of this exoskeleton. Furthermore, the results of the parametrization allow the exoskeleton adaptable to any type of dimensions that the mannequin could have. The final model obtained has been exported to IPS IMMA and implemented in a mannequin.

Colonoscopy provides a minimally invasive tool for examining and treating the colon without surgery, but current endoscope designs still cause a degree of pain and injury to the colon wall. The most common colonoscopies are long tubes inserted through the rectum, with locomotion actuators, fiber optic lights, cameras, and biopsy tools on the distal end. The stiffness required to support these tools makes it difficult for the scopes to navigate the twisted path of the colon without damaging the inside wall of the colon or distorting its shape. In addition, little is known about how sharp and forceful endoscopes can be without accidentally cutting into tissue during navigation. In order to solve the requirements of stiffness (to support tools) and flexibility (to navigate turns), we expanded on a design by Zehel et al. [49], who proposed surrounding a flexible endoscope with an external exoskeleton structure, with controllable stiffness. The exoskeleton structure is comprised of rigid, articulating tubular units, which are stiffened or relaxed by four control cables. The stiffened or locked exoskeleton structure aids navigation and provides stability for the endoscope when it protrudes beyond the exoskeleton structure for examination and procedures. This research determined the design requirements of such an exoskeleton structure and simulated its behavior in a sigmoid colon model. To predict just how pointed an endoscope can be without damaging tissue under a given force, we extrapolated a strength model of the descending colon from published stress-strain curves of human colon tissue. Next we analyzed how friction, cable forces, and unit angles interact to hold the exoskeleton structure in a locked position. By creating two- and three-dimensional models of the exoskeleton structure, we optimized the dimensions of the units of an exoskeleton structure (diameter, thickness, and leg angle) and cable holders ( cable attachment location) to achieve the turns of the sigmoid colon, while still remaining lockable. Models also predicted the loss of force over the exoskeleton structure due to curving, further determining the required cable angles and friction between units. Finally we determined how the stiffness of the endoscope stem affected locking ability and wear inside the exoskeleton structure. / Ph. D.

Knee osteoarthritis (KOA) is the primary cause of chronic immobility in populations over the age of 65. It is a joint degenerative disease in which the articular cartilage in the knee joint wears down over time, leading to symptoms of pain, instability, joint stiffness, and misalignment of the lower extremities. Without intervention, these symptoms gradually worsen over time, decreasing the overall knee range of motion (ROM) and ability to walk. Current clinical interventions include offloading braces, which mechanically realign the lower extremities to alleviate the pain experienced in the medial compartment of the knee joint. Though these braces have proven effective in pain management, studies have shown a significant decrease in knee ROM while using the brace. Concurrently, development of active exoskeletons for rehabilitative gait has increased within recent years in efforts to provide patients with a more effective intervention for dealing with KOA. Though some developed exoskeletons are promising in their efficacy of fostering gait therapy, these devices are heavy, tethered, difficult to control, unavailable to patients, or costly due to the number of complicated components used to manufacture the device. However, the idea that an active component can improve gait therapy for patients motivates this study. This study proposes the design of an adjustable lower extremity exoskeleton which features a single linear actuator adapted onto a commercially available offloading brace. This design hopes to provide patients with pain alleviation from the brace, while also actively driving the knee through flexion and extension. The design and execution of this exoskeleton was accomplished by 3D computer simulation, 3D CAD modeling, and rapid prototyping techniques. The exoskeleton features 3D printed, ABS plastic struts and supports to achieve successful adaptation of the linear actuator to the brace and an electromechanical system with a rechargeable operating capacity of 7 hours. Design validation was completed by running preliminary gait trials of neutral gait (without brace or exoskeleton), offloading brace, and exoskeleton to observe changes between the different gait scenarios. Results from this testing on a single subject show that there was an observed, significant decrease in average knee ROM in the offloading brace trials from the neutral trials and an observed, significant increase in average knee ROM in the exoskeleton trials when compared to the brace trials as hypothesized. Further evaluation must be completed on the clinical efficacy of this device with a larger, and clinically relevant sample size to assess knee ROM, pain while using the device, and overall comfort level. Further development of this design could focus on material assessment, cost analysis, and risk mitigation through failure mode analysis.

Ankle exoskeletons are designed to help people with movement weakness to restore the walking ability . However, people with gait pathology, for instance, drop foot, usually have difficulties in lifting the front part of foot during gait. Thus, different from health subjects, both plantarflexion and dorsiflexion assistance are needed for them to walk better. The purpose of this thesis is to implement an EMG-­driven control strategy for a cable­driven ankle exoskeleton while exploring the use of reinforcement learning in exoskeleton control. The work uses an EMG­-driven musculoskeletal model to predict ankle joint torque. The model uses EMG signals from 4 lower­-limb muscles related to plantarflexion and dorsiflexion to obtain ankle torque and stiffness. The dynamic model for an ankle exoskeleton is built for simulation. The reinforcement learning controller is designed for the ankle exoskeleton tracking the desired ankle joint torques. Based on simulation results, two main conclusions can be drawn, one is that the proposed control strategy can provide precise torque assistance; the other is that using reinforcement learning to track the desired assistive trajectories is effective. / Ankel exoskeletons är utformade för att hjälpa människor med rörelsessvaghet att återställa gångförmågan. Men personer med gångpatologi, till exempel faller fot, har vanligtvis svårt att lyfta den främre delen av foten under gång. Således, annorlunda än hälsoämnen, behövs både plantarflexion- och dorsiflexionshjälp för att de ska kunna gå bättre. Syftet med denna avhandling är att implementera en EMG­-driven kontrollstrategi för ett kabeldrivet vristexoskelet samtidigt som man utforskar användningen av förstärkningsinlärning vid exoskeletskontroll. Arbetet använder en EMG­-driven muskuloskeletal modell för att förutsäga fotledets vridmoment. Modellen använder EMG-­signaler från 4 nedre extremiteter muskler relaterade till plantarflexion och dorsiflexion för att uppnå vridmoment och styvhet. Den dynamiska modellen för ett fotoskeleton är byggd för simulering. Förstärkningsinlärningskontrollern är utformad för fotledets exoskelett som spårar önskade vridmoment i fotleden. Baserat på simuleringsresultat kan två huvudsakliga slutsatser dras, en är att den föreslagna kontrollstrategin kan ge exakt momenthjälp; den andra är att det är effektivt att använda förstärkningslärande för att spåra de önskade hjälpbanorna.

This thesis presents an impedance control strategy for a novel powered hip exoskeleton designed to provide partial assistance and leverage the dynamics of human gait. The control strategy is based on impedance control and provides the user assistance as needed which is determined by the user’s interaction with the exoskeleton. A series elastic element is used to drive the exoskeleton and measures the interaction torque between the user and the device. The device operates in two modes. Free mode is a low impedance state that attempts to provide no assistance. Assist mode increases the gains of the controller to provide assistance as needed. The device was tested on five healthy subjects, and the resulting assistive hip torque was evaluated to determine the ability of the controller to provide gait assistance. The device was evaluated at different speeds to assess the gait speed adaptation performance of the controller. Results show that hip torque assistance range was between 0.3 to 0.5 Nm/kg across the subjects, corresponding to 24% to 40% of the maximum hip torque requirements of healthy adults during walking. The peak power provided by the system is 35 W on average and a peak power of up to 45 W.

As a valuable asset in human augmentation and medical rehabilitation, exoskeletons have become a major area for research and development. They have shown themselves to be effective tools for training and rehabilitation of individuals suffering from limited mobility. However, most exoskeletons are not capable of balancing without the assistance of crutches from the user. Leveraging technology and techniques developed for force controlled humanoid robots, a project was undertaken to develop a fully self-balancing, compliant lower-body robotic exoskeleton. Due to their many beneficial features, series elastic actuators were utilized to power the joints on the exoskeleton. This thesis details the development of four linear series elastic actuators (LSEA) as part of this project. All 12-degrees of freedom will be powered by one of these four LSEA's. Actuator requirements were developed by examining human gait data and three robot-walking simulations. These four walking scenarios were synthesized into one set of power requirements for actuator development. Using these requirements, analytical models were developed to perform component trade studies and predict the performance of the actuator. These actuators utilize high-efficacy components, parallel electric motors, and liquid cooling to attain high power-to-weight ratios, while maintaining a small lightweight design. These analyses and trade studies have resulted in the design of a dual-motor liquid-cooled actuator capable of producing a peak force 8500N with a maximum travel speed of 0.267m/s, and three different single-motor actuators capable of producing forces up to 2450N continuously, with a maximum travel speeds up to 0.767m/s. / Master of Science / Patients who suffer a severe back injury that results in paralysis from the waist down (paraplegia) commonly regain mobility in their daily lives by using a wheelchair. However, staying in a seated position for long periods can cause serious medical issues to arise. In order to address these issues, lower-body exoskeletons have been developed to help patients walk again. Exoskeletons are mechanical devices a person can wear to enhance their physical strength or endurance beyond their normal capability. These exoskeletons have shown themselves to be effective tools for training and rehabilitation of individuals suffering from limited mobility. However, most exoskeletons are not capable of balancing the user while they walk. In order to maintain balance, the user must hold themselves up with crutches. As with a wheelchair, heavy dependence on crutches can lead to new medical issues for the patient. To solve this problem, technology and techniques created for humanoid robots were used to develop a fully self-balancing exoskeleton. This exoskeleton is known as the Orthotic Lower-body Locomotion Exoskeleton. This thesis details the development of four actuators to power all twelve joints of the exoskeleton. These actuators utilize high-efficiency components, multiple electric motors, and liquid cooling to maintain a small lightweight design and while obtaining very high-power outputs.

Nesta tese de doutorado são apresentados sistemas globais de estimativa baseados em modelos Markovianos aplicados na área de reabilitação robótica. Os sistemas propostos foram desenvolvidos para estimar as posições angulares dos elos de exoesqueletos para membros inferiores, desenvolvidos para reabilitação motora em pacientes que sofreram Acidente Vascular Cerebral (AVC) ou lesão medular. Filtros baseados no filtro de Kalman, um nominal e outro considerando incertezas no modelo, foram utilizados em estratégias de fusão de dados de sensores provenientes de sensores inerciais, possibilitando estimativas de posicionamentos angulares. Algoritmos genéticos são utilizados na otimização dos filtros, ajustando as matrizes de peso destes. Em oposição as modelagens tradicionais, via estimativa local, utilizando somente uma unidade inercial para cada modelo, propõe-se um sistema global de estimativa, obtendo-se a melhor informação de cada sensor combinando-os em um modelo Markoviano. Resultados experimentais com um exoesqueleto foram utilizados para comparar a abordagem Markoviana às convencionais. / In this thesis are presented global estimation systems based on Markov models applied in robotic rehabilitation area. The proposed systems have been developed to estimate the angular positions of the exoskeletons for lower limbs, designed to provide motor rehabilitation of stroke and spinal cord injured people. Filters based on the Kalman filter, one nominal and other considering uncertainties in the model, were used in sensor data fusion strategies from inertial sensors, to estimate angular positions. Genetic algorithms are used to the optimization of filters, tuning the weighting matrices. In opposition to these modelling via local estimation, using only one inertial unit, we also chose a global modelling getting the best information from each sensor, combining them in a Markov model. Experimental results with an exoskeleton were used to compare the Markovian approach to conventional.

Este trabalho apresenta o desenvolvimento de algoritmos de adaptação do padrão de marcha com a utilização de redes neurais artificiais para uma órtese ativa para membros inferiores. Trajetórias estáveis são geradas durante o processo de otimização, considerando um gerador de trajetórias baseado no critério do ZMP (Zero Moment Point) e no modelo dinâmico do equipamento. Três redes neurais são usadas para diminuir o tempo de cálculo do modelo e da otimização do ZMP, e reproduzir o gerador de trajetórias analítico. A primeira rede aproxima a dinâmica do modelo fornecendo a variação de torque necessária para a realização do processo de otimização dos parâmetros de adaptação da marcha; a segunda rede trabalha no processo de otimização, fornecendo o parâmetro otimizado de acordo com a interação paciente-órtese; a terceira rede reproduz o gerador de trajetórias para um determinado intervalo de tempo do passo que pode ser repetido para qualquer quantidade de passos. Além disso, um controle do tipo torque calculado acrescido de um controle PD é usado para garantir que as trajetórias atuais estejam seguindo as trajetórias desejadas da órtese. O modelo dinâmico da órtese na sua configuração atual, com forças de interação incluídas, é usado para gerar resultados simulados. / This work deals with neural network-based gait-pattern adaptation algorithms for an active lower limbs orthosis. Stable trajectories are generated during the optimization process, considering a trajectory generator based on the Zero Moment Point criterion and on the dynamic model. Additionally, three neural network are used to decrease the time-consuming computation of the model and ZMP optimization and to reproduce the analitical trajectory generator. The first neural network approximates the dynamic model providing the necessary torque variation to gait adaptation parameters process; the second network works in the optimization procedure, giving the adapting parameter according to orthosis-patient interaction; and the third network replaces the trajectory generation for a stablished step time interval which can be reproduced any time during the walking. Also, a computed torque controller plus the PD controller is designed to guarantee the actual trajectories are following the orthosis desired trajectories. The dynamic model of the actual active orthosis, with interaction forces included, is used to generate simulation results.