1,461 research outputs found

    Switched Kinematic and Force Control for Lower-Limb Motorized Exoskeletons and Functional Electrical Stimulation

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    Millions of people experience movement deficits from neurological conditions (NCs) that impair their walking ability and leg function. Exercise-based rehabilitation procedures have shown the potential to facilitate neurological reorganization and functional recovery. Lower-limb powered exoskeletons and motorized ergometers have been combined with functional electrical stimulation (FES) to provide repetitive movement, partially reduce the burden of therapists, improve range of motion, and induce therapeutic benefits. FES evokes artificial muscles contractions and can improve muscle mass and strength, and bone density in people with NCs. Stationary cycling is recommended for individuals who cannot perform load-bearing activities or have increased risks of falling. Cycling has been demonstrated to impart physiological and cardiovascular benefits. Motorized FES-cycling combines an electric motor and electrical stimulation of lower-limb muscles to facilitate coordinated, long-duration exercise, while mitigating the inherent muscle fatigue due to FES. Lower-limb exoskeletons coupled with FES, also called neuroprostheses or hybrid exoskeletons, can facilitate continuous, repetitive motion to improve gait function and build muscle capacity. The human-robot interaction during rehabilitative cycling and walking yield a mix of discrete effects (i.e., foot impact, input switching to engage lower-limb muscles and electric motors, etc.) and continuous nonlinear, uncertain, time-varying dynamics. Switching control is necessary to allocate the control inputs to lower-limb muscle groups and electric motors involved during assisted cycling and walking. Kinematic tracking has been the primary control objective for devices that combine FES and electric motors. However, there are force interactions between the machine and the human during cycling and walking that motivate the design of torque-based controllers (i.e., exploit torque or force feedback) to shape the leg dynamics through controlling joint kinematics and kinetics. Technical challenges exist to develop closed-loop feedback control strategies that integrate kinematic and force feedback in the presence of switching and discontinuous effects. The motivation in this dissertation is to design, analyze and implement switching controllers for assisted cycling and walking leveraging kinematic and force feedback while guaranteeing the stability of the human-robot closed-loop system. In Chapter 1, the motivation to design closed-loop controllers for motorized FES-cycling and powered exoskeletons is described. A survey of closed-loop kinematic and force feedback control methods is also introduced related to the tracking objectives presented in the subsequent chapters of the dissertation. In Chapter 2, the dynamics models for walking and assisted cycling are described. First, a bipedal walking system model with switched dynamics is introduced to control a powered lower-limb exoskeleton. Then, a stationary FES-cycling model with nonlinear dynamics and switched control inputs is 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. The experimental setup for lower-limb exoskeleton and FES-cycling are described. In Chapter 3, a hierarchical control strategy is developed to interface a cable-driven lower-limb exoskeleton. A two-layer control system is developed to adjust cable tensions and apply torque about the knee joint using a pair of electric motors that provide knee flexion and extension. The control design is segregated into a joint-level control loop and a low-level loop using feedback of the angular positions of the electric motors to mitigate cable slacking. A Lyapunov-based stability analysis is developed to ensure exponential tracking for both control objectives. Moreover, an average dwell time analysis computes an upper bound on the number of motor switches to preserve exponential tracking. Preliminary experimental results in an able-bodied individual are depicted. The developed control strategy is extended and applied to the control of both knee and hip joints in Chapter 4 for treadmill walking. In Chapter 4, a cable-driven lower-limb exoskeleton is integrated with FES for treadmill walking at a constant speed. A nonlinear robust controller is used to activate the quadriceps and hamstrings muscle groups via FES to achieve kinematic tracking about the knee joint. Moreover, electric motors adjust the knee joint stiffness throughout the gait cycle using an integral torque feedback controller. A Lyapunov-based stability analysis is developed to ensure exponential tracking of the kinematic and torque closed-loop error systems, while guaranteeing that the control input signals remain bounded. The developed controllers were tested in real-time walking experiments on a treadmill in three able-bodied individuals at two gait speeds. The experimental results demonstrate the feasibility of coupling a cable-driven exoskeleton with FES for treadmill walking using a switching-based control strategy and exploiting both kinematic and force feedback. In Chapter 5, input-output data is exploited using a finite-time algorithm to estimate the target desired torque leveraging an estimate of the active torque produced by muscles via FES. The convergence rate of the finite-time algorithm can be adjusted by tuning selectable parameters. To achieve cadence and torque tracking for FES-cycling, nonlinear robust tracking controllers are designed for muscles and motor. A Lyapunov-based stability analysis is developed to ensure exponential tracking of the closed-loop cadence error system and global uniformly ultimate bounded (GUUB) torque tracking. A discrete-time Lyapunov-based stability analysis leveraging a recent tool for finite-time systems is developed to ensure convergence and guarantee that the finite-time algorithm is Holder continuous. The developed tracking controllers for the muscles and electric motor and finite-time algorithm to compute the desired torque are implemented in real-time during cycling experiments in seven able-bodied individuals. Multiple cycling trials are implemented with different gain parameters of the finite-time torque algorithm to compare tracking performance for all participants. Chapter 6 highlights the contributions of the developed control methods and provides recommendations for future research extensions

    Sensory Electrical Stimulation Improves Foot Placement during Targeted Stepping Post-Stroke

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    Proper foot placement is vital for maintaining balance during walking, requiring the integration of multiple sensory signals with motor commands. Disruption of brain structures post-stroke likely alters the processing of sensory information by motor centers, interfering with precision control of foot placement and walking function for stroke survivors. In this study, we examined whether somatosensory stimulation, which improves functional movements of the paretic hand, could be used to improve foot placement of the paretic limb. Foot placement was evaluated before, during, and after application of somatosensory electrical stimulation to the paretic foot during a targeted stepping task. Starting from standing, twelve chronic stroke participants initiated movement with the non-paretic limb and stepped to one of five target locations projected onto the floor with distances normalized to the paretic stride length. Targeting error and lower extremity kinematics were used to assess changes in foot placement and limb control due to somatosensory stimulation. Significant reductions in placement error in the medial–lateral direction (p = 0.008) were observed during the stimulation and post-stimulation blocks. Seven participants, presenting with a hip circumduction walking pattern, had reductions (p = 0.008) in the magnitude and duration of hip abduction during swing with somatosensory stimulation. Reductions in circumduction correlated with both functional and clinical measures, with larger improvements observed in participants with greater impairment. The results of this study suggest that somatosensory stimulation of the paretic foot applied during movement can improve the precision control of foot placement

    Switching Adaptive Concurrent Learning Control for Powered Rehabilitation Machines with FES

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    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

    Robotic Rehabilitation Devices of Human Extremities: Design Concepts and Functional Particularities

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    International audienceAll over the world, several dozen million people suffer from the effects of post-polio, multiple sclerosis, spinal cord injury, cerebral palsy, etc. and could benefit from the advances in robotic devices for rehabilitation. Thus, for modern society, an important and vital problem of designing systems for rehabilitation of human physical working ability appears. The temporary or permanent loss of human motor functions can be compensated by means of various rehabilitation devices. They can be simple mechanical systems for orthoses, which duplicate the functions of human extremities supplying with rigidity and bearing capacity or more complex mechatronic rehabilitation devices with higher level of control. We attempt to cover all of the major developments in these areas, focusing particularly on the development of the different concepts and their functional characteristics. The robotic devices with several structures are classified, taking into account the actuation systems, the neuromuscular stimulations, and the structural schemes. It is showed that the problems concerning the design of rehabilitation devices are complex and involve many questions in the sphere of biomedicine, mechanics, robot technology, electromechanics and optimal control. This paper provides a design overview of hardware, actuation, sensory, and control systems for most of the devices that have been described in the literature, and it ends with a discussion of the major advances that have been made and should be yet overcome

    Rehabilitation of gait after stroke: a review towards a top-down approach

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    This document provides a review of the techniques and therapies used in gait rehabilitation after stroke. It also examines the possible benefits of including assistive robotic devices and brain-computer interfaces in this field, according to a top-down approach, in which rehabilitation is driven by neural plasticity

    Robotic design and modelling of medical lower extremity exoskeletons

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    This study aims to explain the development of the robotic Lower Extremity Exoskeleton (LEE) systems between 1960 and 2019 in chronological order. The scans performed in the exoskeleton system’s design have shown that a modeling program, such as AnyBody, and OpenSim, should be used first to observe the design and software animation, followed by the mechanical development of the system using sensors and motors. Also, the use of OpenSim and AnyBody musculoskeletal system software has been proven to play an essential role in designing the human-exoskeleton by eliminating the high costs and risks of the mechanical designs. Furthermore, these modeling systems can enable rapid optimization of the LEE design by detecting the forces and torques falling on the human muscles

    Evidence for early physiotherapy after acute stroke: a scoping review

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    Neuroscience evidence indicates that early rehabilitation can guarantee better outcomes and quicker cortical re-organization after lesion. Although there are some studies related to the acute stroke physiotherapy intervention, it seems that few consider the evidence that link neuroplasticity and neurorehabilitation. Therefore, understanding the current state of the art of physiotherapy intervention is vital to potentialize the intervention so the enhance neuroplastic window is properly explored. To analyze the physiotherapy's intervention on acute stroke patients, so it reveals the underlined evidence for the selection of the approach and if the neurophysiological mechanisms are associated. This scoping review's methodology follows the Joanna Briggs Institue. A main search was conducted across Pubmed, PEdro and Web of science in December 2020, including only studies in Portuguese or English. Studies included focused on the concept of physiotherapy's intervention in a population of adult acute stroke patients, in an acute care context. Were identified 14 categories of interventions in 37 studies. 62% of studies didn't give any justification for the choic of method and the ones who did, weren't focused on neurophysiological knowledge. A wide range of interventions was found in which only 38% showed justifications that were considered insufficient and imprecise

    Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation

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    Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration

    Noninvasive Modalities Used in Spinal Cord Injury Rehabilitation

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    In the past three decades, research on plasticity after spinal cord injury (SCI) has led to a gradual shift in SCI rehabilitation: the former focus on learning compensatory strategies changed to functional neurorecovery, that is, promoting restoration of function through the use of affected limbs. This paradigm shift contributed to the development of technology-based interventions aiming to promote neurorecovery through repetitive training. This chapter presents an overview of a range of noninvasive modalities that have been used in rehabilitation after SCI. Among others, we present repetitive transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), surface electrical stimulation tools such as transcutaneous electrical spinal cord stimulation (tcSCS), transcutaneous electrical nerve stimulation (TENS), and functional electrical stimulation (FES), as well as its integration with cycling training and assistive robotic devices. The most recent results attained and the potential relevance of these new techniques to strengthen the efficacy of the residual neuronal pathways and improve spasticity are also presented. Future efforts toward the widespread clinical application of these modalities include more advances in the technology, together with the knowledge obtained from basic research and clinical trials. This can ultimately lead to novel customized interventions that meet specific needs of SCI patients

    Hybrid Neuroprosthesis for Lower Limbs

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    Assistive technologies have been proposed for the locomotion of people with spinal cord injury (SCI). One of them is the neuroprosthesis that arouses the interest of developers and health professionals bearing in mind the beneficial effects promoted in people with SCI. Thus, the first session of this chapter presents the principles of human motility and the impact that spinal cord injury causes on a person’s mobility. The second session presents functional electrical stimulation as a solution for the immobility of paralyzed muscles. It explains the working principles of constituent modules and main stimulatory parameters. The third session introduces the concepts and characteristics of neural prosthesis hybridization. The last two sessions present and discuss examples of hybrid neuroprostheses. Such systems employ hybrid assistive lower limb strategies to evoke functional movements in people with SCI, associating the motor effects of active and/or passive orthoses to a functional electrical stimulation (FES) system. Examples of typical applications of FES in rehabilitation are discussed
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