15 research outputs found

    Robust Control of the Knee Joint Angle of Paraplegic Patients considering Norm-Bounded Uncertainties

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    A proposal for the knee position control design of paraplegic patients with functional electrical stimulation (FES) using control systems and considering norm-bounded uncertainties is presented. A state-space representation of the knee joint model of the paraplegic patient with its nonlinearity is also demonstrated. The use of linear matrix inequalities (LMIs) in control systems with norm-bounded uncertainties for asymptotic stability is analyzed. The model was simulated in the Matlab environment. The matrix K of state space feedback was obtained through LMIs

    Design and Control of Lower Limb Assistive Exoskeleton for Hemiplegia Mobility

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    Analysis and control of FES-assisted paraplegic walking with wheel walker.

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    The number of people with spinal cord injury (SCI) is increasing every year and walking has been found to be the most exciting and important prospect to these patients to improve their quality of life. Many individuals with incomplete SCI have the potential to walk and everyone of them wants to try. Unfortunately up to now, there is less than one third of patients could walk again after SCI. Residual function, the orthotic support, energy expenditure, patient motivation and control technique are some of the factors that influence the walking outcome of spinal cord injured people. In this thesis, a series of studies are carried out to investigate the possibility of enhancing the performance of the functional electrical stimulation (PES) assisted paraplegic walking with wheel walker through the development and implementation of intelligent control technique and spring brake orthosis (SBO) with full utilization of the voluntary upper body effort. The main aim of this thesis is to enable individuals with complete paraplegia to walk again with maximum performance and the simplest approach as possible. Firstly, before simulation of the system can be made, it is important to select the right model to represent the actual plant. In this thesis, the development of a humanoid and wheel walker models are carried out using MSC.visualNastran4D (vN4D) software and this is integrated with Matlab Simulink® for simulation. The newly developed quadriceps and hamstrings muscle models from the series of experiments are used to represent subject muscles after comparison and validation with other two well-known muscle models are performed. Several experiments are conducted to investigate the effect of stimulation frequency and pulse-width in intermittent stimulation with isometric measurement from paraplegic subjects. The results from this work can serve as a guidance to determine the optimum stimulation parameters such as frequency and pulse-width to reduce muscle fatigue during PES application. The ability test is introduced to determine the maximum leg force that can be applied to the specific paraplegic subject during FES functional task with minimum chance of spasm and leg injury. Investigations are carried out on the control techniques implemented for FES walking with wheel walker. PID control and fuzzy logic control (FLC) are used to regulate the electrical stimulation required by the quadriceps and hamstrings muscles in order to perform the FES walking manoeuvre according to predefined walking trajectory. The body weight transfer is introduced to increase the efficiency of FES walking performance. The effectiveness of body weight transfer and control strategy to enhance the performance of FES walking and reduce stimulation pulses required is examined. Investigations are carried out on the effectiveness of spring brake orthosis (SBO) for FES assisted paraplegic walking with wheel walker. A new concept in hybrid orthotics provides solutions to the problems that affect current 'hybrid orthosis, including knee and hip flexion without relying on the withdrawal reflex or a powered actuator and foot-ground clearance without extra upper body effort. The use of SBO can also eliminate electrical stimulation pulses required by the hamstrings muscle for the same FES walking system. Further improvement of the FES walking system is achieved by introducing finite state control (FSC) to control the switching time between springs, brakes and electrical stimulation during FES assisted walking with wheel walker with the combInation of FLC to regulate the electrical stimulation required for the knee extension. The results show that FSC can be used to accurately control the switching time and improve the system robustness and stability

    Using primary afferent neural activity for predicting limb kinematics in cat

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    Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, these methods did not make efficient use of the information embedded in the firing rates of the neural population. This dissertation proposes new methods for decoding limb kinematics from primary afferent firing rates. We present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of primary afferent neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. This thesis further explores the feasibility of decoding primary afferent firing rates in the presence of stimulation artifact generated during functional electrical stimulation. We show that kinematic information extracted from the firing rates of primary afferent neurons can be used in a 'real-time' application as a feedback for control of FES in a neuroprostheses. It provides methods for decoding primary afferent neurons and sets a foundation for further development of closed loop FES control of paralyzed extremities. Although a complete closed loop neuroprosthesis for natural behavior seems far away, the premise of this work argues that an interface at the dorsal root ganglia should be considered as a viable option

    Modelling and Control of Lower Limb Exoskeletons and Walking Aid for Fundamental Mobility Tasks

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    The Mechanical Design and Analysis of an Active Prosthetic Knee

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    In a world of war and turmoil in developing nations, land mines are becoming a concern, as millions of them are scattered in countries all over the world. Moreover, land mine prevention programs cannot clear land mine fields as fast as they are detonated each day. As a result, there are thousands that fall victim each year. There is immense demand for newer technologies to replace the aging prostheses used in these war torn nations. The active prosthetic knee (APK) design project is a novel design that utilizes simple, robust one degree of freedom (DOF) mechanics, while providing fully active knee torque control. The APK utilizes a high-speed brushed servomotor, providing the necessary torque and dynamics to provide the necessary gait characteristics of human locomotion. The main research contributions of this thesis are: 1) the mechanics and 2) the intelligence of the APK. This thesis investigates and highlights the prosthetic’s design process. The human biological system is studied and used as the design criteria when designing the device. Anthropometric data was used to determine the sizing and other physical properties. Moreover, Adaptive-Network-based Fuzzy-Interference Systems (ANFIS) and Fuzzy Interference Systems (FIS) are used to provide control to the APK. Finite element analysis (FEA) verifies the structural integrity of the APK. Four simulations are analyzed: equivalent stress, equivalent strain, shear stress and total deformation. These four simulations provide a mathematical interpretation of the physical system. We found that the first prototype, although a sound design, can be further improved to allow greater loading capabilities. Moreover, cyclical loading and total life cycles would also be significantly improved. A modular test stand is also designed and prototyped to allow APK testing. Since the APK prototype cannot be immediately placed on a human test subject, the test stand allows for experimentation in replicating human gait cycles

    The Development of an assistive chair for elderly with sit to stand problems

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    A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyStanding up from a seated position, known as sit-to-stand (STS) movement, is one of the most frequently performed activities of daily living (ADLs). However, the aging generation are often encountered with STS issues owning to their declined motor functions and sensory capacity for postural control. The motivated is rooted from the contemporary market available STS assistive devices that are lack of genuine interaction with elderly users. Prior to the software implementation, the robot chair platform with integrated sensing footmat is developed with STS biomechanical concerns for the elderly. The work has its main emphasis on recognising the personalised behavioural patterns from the elderly users’ STS movements, namely the STS intentions and personalised STS feature prediction. The former is known as intention recognition while the latter is defined as assistance prediction, both achieved by innovative machine learning techniques. The proposed intention recognition performs well in multiple subjects scenarios with different postures involved thanks to its competence of handling these uncertainties. To the provision of providing the assistance needed by the elderly user, a time series prediction model is presented, aiming to configure the personalised ground reaction force (GRF) curve over time which suggests successful movement. This enables the computation of deficits between the predicted oncoming GRF curve and the personalised one. A multiple steps ahead prediction into the future is also implemented so that the completion time of actuation in reality is taken into account

    INTELLIGENT CONTROL FOR A NOVEL ASSIST MECHANISM IN FUNCTIONAL ELECTRICAL STIMULATION CYCLING

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