In people with neuromotor deficits of trunk and lower extremities, maintaining and regaining balance is a difficult task. Many undergo rehabilitation to improve their movement capabilities, health, and overall interactions with their environment. Rehabilitation consists of a set of interventions designed to improve the individual’s mobility and independence. These strategies can be passive, active or task-specific and are dependent on the type of injury, how the individual progresses, and the intensity of the activity. Some of the common rehabilitation interventions to strengthen muscles and improve coordination are accomplished either by the manual assistance of a physical therapist, bodyweight suspension systems or through robotic-assisted training. There are several types of rehabilitation robotic systems and robotic control strategies.However, there are few robotic studies that compare their robotic device’s control strategy to common rehabilitation interventions. This dissertation introduces robotic strategies centered around rehabilitation ones and characterizes human motion in response to the robotic forces. Two cable-driven robotic systems are utilized to implement the robotic controllers for different tasks. Further details of the two cable-driven systems are discussed in Chapter 1. The validation and evaluation of these robotic strategies for standing rehabilitation is discussed in Chapter 2. A case study of a robotic training paradigm for individuals with spinal cord injury is presented in Chapter 3. Chapter 4 introduces a method to redistribute individuals’ weight using pelvic lateral forces. Chapter 5 and 6 characterizes how young and older groups respond to external perturbations during their sit-to-stand motion. This dissertation presents robotic strategies that can be implemented as rehabilitation interventions. It also presents how individuals’ biomechanics and muscle responses may change depending on the force control paradigm.These robotic strategies can be utilized by training individuals to improve their reactive and active balance control and thus reduce their risk of falling.

Thesis (MScEng)--Stellenbosch University, 2009. / ENGLISH ABSTRACT: Minimal invasive surgery (MIS) enables surgeons to operate through a few small incisions made in the patient’s body. Through these incisions, long rigid instruments are inserted into the body and manipulated to perform the necessary surgical tasks. Conventional instruments, however, are constrained by having only five degrees of freedom (DOF), as well as having scaled and mirrored movements, thereby limiting the surgeon’s dexterity. Surgeons are also deprived of depth perception and hand-eye coordination due to only having two-dimensional visual feedback. Surgical robotics attempt to alleviate these drawbacks by increasing dexterity, eliminating the fulcrum effect and providing the surgeon with three-dimensional visualisation. This reduces the risks to the patient as well as to the surgeon. However, existing MIS systems are extremely expensive and bulky in operating rooms, preventing their more widespread adoption. In this thesis, a new, inexpensive seven-DOF primary slave manipulator (PSM) is presented. The four-DOF wrist is actuated through a tendon mechanism driven by five 12 VDC motors. A repeatability study on the wrist’s joint position was done and showed a standard deviation of 0.38 degrees. A strength test was also done and demonstrated that the manipulator is able to resist a 10 N opposing tip force and is capable of a theoretical gripping force of 15 N. / AFRIKAANSE OPSOMMING: Minimale indringende chirurgie (MIC) maak dit vir chirurge moontlik om operasies uit te voer deur ’n paar klein insnydings wat op die pasiënt se liggaam gemaak word. Deur hierdie insnydings word lang onbuigsame instrumente in die liggaam ingesit en gemanipuleer om die nodige chirurgiese take uit te voer. Konvensionele instrumente is egter beperk vanweë die feit dat hulle net vyf vryheidsgrade het, asook afgeskaalde bewegings en spieëlbewegings, en gevolglik die chirurg se handvaardigheid beperk. Chirurge word ook ontneem van dieptewaarneming en hand-oog-koördinasie, want hulle is beperk tot tweedimensionele visuele terugvoer. Chirurgiese robotika poog om hierdie nadele aan te spreek deur handvaardigheid te vermeerder, die hefboomeffek uit te skakel en die chirurg driedimensionele visualisering te bied. Dit verminder die risiko’s vir die pasiënt én vir die chirurg. Bestaande MIC-stelsels is egter uiters duur en neem baie plek op in teaters, wat verhoed dat hulle op ’n groter skaal gebruik word. In hierdie tesis word ’n nuwe, goedkoop sewevryheidsgrade- primêre slaafmanipuleerder (PSM) voorgelê. Die viervryheidsgrade-pols word beweeg deur ’n tendonmeganisme wat aangedryf word deur vyf 12 VDC-motors. ’n Herhaalbaarheidstudie is op die pols se gewrigsposisie gedoen, wat ’n standaardafwyking van 0.38 grade aangetoon het. ’n Sterktetoets is ook gedoen en het gewys dat die manipuleerder in staat is om ’n 10 N-teenkantelkrag te weerstaan en dat dit oor ’n teoretiese greepsterkte van 15 N beskik.

Biological systems are able to perform complex movements with high energy-efficiency and, in general, can adapt to environmental changes more elegantly than traditionally engineered mechanical systems. The Equilibrium Point Hypothesis describes animal motor control as trajectories of equilibrium joint angle and joint stiffness. Traditional approaches to robot design are unable to implement this control scheme because they lack joint actuation methods that can control mechanical stiffness, and, in general, they are unable to take advantage of energy introduced into the system by the environment. In this paper, we describe the development and implementation of an FPGA-controlled, servo-actuated robotic joint that incorporates series-elastic actuation with specially developed nonlinear springs. We show that the joint's equilibrium angle and stiffness are independently controllable and that their independence is not lost in the presence of external joint torques. This approach to joint control emulates the behavior of antagonistic muscles, and thus produces a mechanical system that demonstrates biological similarity both in its observable output and in its method of control.

Orientador: João Maurício Rosário / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-24T03:06:34Z (GMT). No. of bitstreams: 1 Floriano-Batista_Rayanne_M.pdf: 3969597 bytes, checksum: fb7104633c8e24f84be507eaef10073d (MD5) Previous issue date: 2013 / Resumo: Nesta dissertação realiza-se um estudo cinemático e dinâmico da marcha humana tendo como base a biomecânica e a antropomorfia dos membros inferiores, assim como nos paradigmas que regem a reabilitação assistida por meio da robótica. Propõe-se uma estratégia de controle de um exoesqueleto robótico para membros inferiores através do cálculo do torque computado, com a finalidade terapêutica de reabilitação da marcha. Adota-se a marcha dinâmica como inspiração para o modelo do sistema, usando uma estrutura simplificada que atuará em dois modos de funcionamento, onde a transição entre um módulo e outro será controlada por meio do formalismo de sistema de eventos. O sistema foi modelado a partir do desenvolvimento de suas equações dinâmicas e implementação em Matlab®, como também através do uso da plataforma SimMechanics® que permitiu a modelagem de componentes externas com maior grau de complexidade. Através de simulação computacional verificou-se que sistema em estudo apresentou um desempenho preciso no desenvolvimento da marcha, onde se considerou, inclusive, os efeitos do impacto que ocorrem a partir da interação do pé com solo / Abstract: In this dissertation is executed a cinematic and dynamic study of human's gait based on the field of knowledge of biomechanics and the anthropomorphic characteristics of human's leg, based as well on paradigms the rules the assisted rehabilitation with the use of robots. Here it's proposed and strategy of control of robotic exoskeletons for lower limbs through the computed torque with therapeutic goal to improve the human gait. The dynamic gait inspire the system's model, it's used a simplified structure which will function in two distinctive modes of operation, the transition between the modes is control by a system of discrete events. The modeled system is developed from its dynamic equations in Matlab® and also with the use of SimMechanics® simulation platform the allowed the inclusion of external components with greater complexity in the model. Through the computational simulation is concluded that the studied system had a precise performance in development of the gait, the control simulation included the effects of the impact that occurs when the foot interact with the solo / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestra em Engenharia Mecânica

This work describes a self-sensing technique for a piezoelectrically driven MRI-compatible tweezer style end effector, suitable for robot assisted, MRI guided surgery. Nested strain amplification mechanisms are used to amplify the displacement of the piezo actuators to practical levels for robotics. By using a hysteretic piezoelectric model and a two port network model for the compliant nested strain amplifiers, it is shown that force and displacement at the tweezer tip can be estimated if the input voltage and charge are measured. One piezo unit is used simultaneously as a sensor and an actuator, preserving the full actuation capability of the device. Experimental validation shows an average of 12% error between the self-sensed and true values.

Teleoperation systems have been used in the operating rooms for more than a decade. However, the lack of force feedback in commercially available systems still raises safety issues and forbids surgical gestures like palpation. Although force feedback has already been implemented in experimental setups, a systematic methodology is still lacking to design the control laws.<p><p>The approach developed in this thesis is a contribution towards such a systematic<p>methodology: it combines the use of disturbance observers with the use of a structured fixed-order controller. This approach is validated by experiments performed on a one degree of freedom teleoperation system. A physical model of this system is proposed and validated experimentally.<p><p>Disturbance observers allow to compensate friction, which is responsible for performance degradation in teleoperation. Contrary to alternative approaches,they are based on a model of the frictionless mechanical system. This allows to compensate friction with a time varying behavior, which occurs in laparoscopy.<p><p>Parametric uncertainties in this model may lead to an unstable closed-loop. A kind of "separation principle" is provided to decouple the design of the closed-loop system from the design of the observer. It relies on a modified problem statement and on the use of available robust design and analysis tools.<p><p>A new metric is proposed to evaluate the performance of friction compensation systems experimentally. This metric evaluates the ability of a compensation system to linearize a motion system, irrespective of the task and as a function of frequency. The observer-based friction compensation is evaluated with respect to this new metric and to a task-based metric. It correctly attenuates the friction in the bandwidth of interest and significantly improves position and force tracking during a palpation task.<p><p>Structured fixed-order controllers are optimized numerically to achieve robust closed-loop performance despite modeling uncertainty. The structure is chosen among classical teleoperation structures. An efficient algorithm is selected and implemented to design such a controller, which is evaluated for a palpation task. It is compared to a full-order unstructured controller, representative of the design approach that has been used in the teleoperation literature up to now. The comparison highlights the advantages of our new approach: order-reduction steps and counter-intuitive behaviors are avoided. <p><p>A structured fixed-order controller combined with a disturbance observer is implemented during a needle insertion experiment and allowed to obtain excellent performance. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

The goal of this investigation was to explore the efficacy of implementing a rehabilitation robot controlled by a noninvasive brain-computer interface (BCI) to influence brain plasticity and facilitate motor learning. The motivation of this project stemmed from the need to address the population of stroke survivors who have few or no options for therapy. A stroke occurs every 40 seconds in the United States and it is the leading cause of long-term disability [1-3]. In a country where the elderly population is growing at an astounding rate, one in six persons above the age of 55 is at risk of having a stroke. Internationally, the rates of strokes and stroke-induced disabilities are comparable to those of the United States [1, 4-6]. Approximately half of all stroke survivors suffer from immediate unilateral paralysis or weakness, 30-60% of which never regain function [1, 6-9]. Many individuals who survive stroke will be forced to seek institutional care or long-term assistance. Clinicians have typically implemented stroke rehabilitative treatment using active training techniques such as constraint induced movement therapy (CIMT) and robotic therapy [10-12]. Such techniques restore motor activity by forcing the movement of weakened limbs. That active engagement of the weakened limb movement stimulates neural pathways and activates the motor cortex, thus inducing brain plasticity and motor learning. Several studies have demonstrated that active training does in fact have an effect on the way the brain restores itself and leads to faster rehabilitation [10, 13-15]. In addition, studies involving mental practice, another form of rehabilitation, have shown that mental imagery directly stimulates the brain, but is not effective unless implemented as a supplemental to active training [16, 17]. Only stroke survivors retaining residual motor ability are able to undergo active rehabilitative training; the current selection of therapies has overlooked the significant population of stroke survivors suffering from severe control loss or complete paralysis [6, 10]. A BCI is a system or device that detects minute changes in brain signals to facilitate communication or control. In this investigation, the BCI was implemented through an electroencephalograph (EEG) device. EEG devices detect electrical brain signals transmitted through the scalp that corresponded with imagined motor activity. Within the BCI, a linear transformation algorithm converted EEG spectral features into control commands for an upper-limb rehabilitative robot, thus implementing a closed-looped feedback-control training system. The concept of the BCI-robot system implemented in this investigation may provide an alternative to current therapies by demonstrating the results of bypassing motor activity using brain signals to facilitate robotic therapy. In this study, 24 able-bodied volunteers were divided into two study groups; one group trained to use sensorimotor rhythms (SMRs) (produced by imagining motor activity) to control the movement of a robot and the other group performed the 'guided-imagery' task of watching the robot move without control. This investigation looked for contrasts between the two groups that showed that the training involved with controlling the BCI-robot system had an effect on brain plasticity and motor learning. To analyze brain plasticity and motor learning, EEG data corresponding to imagined arm movement and motor learning were acquired before, during, and after training. Features extracted from the EEG data consisted of frequencies in the 5-35Hz range, which produced amplitude fluctuations that were measurably significant during reaching. Motor learning data consisted of arm displacement measures (error) produced during an motor adaptation task performed daily by all subjects. The results of the brain plasticity analysis showed persistent reductions in beta activity for subjects in the BCI group. The analysis also showed that subjects in the Non-BCI group had significant reductions in mu activity; however, these results were likely due to the fact that different EEG caps were used in each stage of the study. These results were promising but require further investigation. The motor learning data showed that the BCI group out-performed non-BCI group in all measures of motor learning. These findings were significant because this was the first time a BCI had been applied to a motor learning protocol and the findings suggested that BCI had an influence on the speed at which subjects adapted to a motor learning task. Additional findings suggested that BCI subjects who were in the 40 and over age group had greater decreases in error after the learning phase of motor assessment. These finding suggests that BCI could have positive long term effects on individuals who are more likely to suffer from a stroke and possibly could be beneficial for chronic stroke patients. In addition to exploring the effects of BCI training on brain plasticity and motor learning this investigation sought to detect whether the EEG features produced during guided-imagery could differentiate between reaching direction. While the analysis presented in this project produced classification accuracies no greater than ~77%, it formed the basis of future studies that would incorporate different pattern recognition techniques. The results of this study show the potential for developing new rehabilitation therapies and motor learning protocols that incorporate BCI.