46 research outputs found

    FITFES: A Wearable Myoelectrically Controlled Functional Electrical Stimulator Designed Using a User-Centered Approach

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    Myoelectrically Controlled Functional Electrical Stimulation (MeCFES) has proven to be a useful tool in the rehabilitation of the hemiplegic arm. This paper reports the steps involved in the development of a wearable MeCFES device (FITFES) through a user-centered design. We defined the minimal viable features and functionalities requirements for the device design from a questionnaire-based survey among physiotherapists with experience in functional electrical stimulation. The result was a necklace layout that poses minimal hindrance to task-oriented movement therapy, the context in which it is aimed to be used. FITFES is battery-powered and embeds a standard low power Bluetooth module, enabling wireless control by using PC/Mobile devices vendor specific built-in libraries. It is designed to deliver a biphasic, charge-balanced stimulation current pulses of up to 113 mA with a maximum differential voltage of 300 V. The power consumption for typical clinical usage is 320 mW at 20mA stimulation current and of less than 10 μW10~\mu \text{W} in sleep mode, thus ensuring an estimated full day of FITFES therapy on a battery charge. We conclude that a multidisciplinary user-centered approach can be successfully applied to the design of a clinically and ergonomically viable prototype of a wearable myoelectrically controlled functional electrical stimulator to be used in rehabilitation

    Development of a hybrid robotic system based on an adaptive and associative assistance for rehabilitation of reaching movement after stroke

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    Stroke causes irreversible neurological damage. Depending on the location and the size of this brain injury, different body functions could result affected. One of the most common consequences is motor impairments. The level of motor impairment affectation varies between post-stroke subjects, but often, it hampers the execution of most activities of daily living. Consequently, the quality of life of the stroke population is severely decreased. The rehabilitation of the upper-limb motor functions has gained special attention in the scientific community due the poor reported prognosis of post-stroke patients for recovering normal upper-extremity function after standard rehabilitation therapy. Driven by the advance of technology and the design of new rehabilitation methods, the use of robot devices, functional electrical stimulation and brain-computer interfaces as a neuromodulation system is proposed as a novel and promising rehabilitation tools. Although the uses of these technologies present potential benefits with respect to standard rehabilitation methods, there still are some milestones to be addressed for the consolidation of these methods and techniques in clinical settings. Mentioned evidences reflect the motivation for this dissertation. This thesis presents the development and validation of a hybrid robotic system based on an adaptive and associative assistance for rehabilitation of reaching movements in post-stroke subjects. The hybrid concept refers the combined use of robotic devices with functional electrical stimulation. Adaptive feature states a tailored assistance according to the users’ motor residual capabilities, while the associative term denotes a precise pairing between the users’ motor intent and the peripheral hybrid assistance. The development of the hybrid platform comprised the following tasks: 1. The identification of the current challenges for hybrid robotic system, considering twofold perspectives: technological and clinical. The hybrid systems submitted in literature were critically reviewed for such purpose. These identified features will lead the subsequent development and method framed in this work. 2. The development and validation of a hybrid robotic system, combining a mechanical exoskeleton with functional electrical stimulation to assist the execution of functional reaching movements. Several subsystems are integrated within the hybrid platform, which interact each other to cooperatively complement the rehabilitation task. Complementary, the implementation of a controller based on functional electrical stimulation to dynamically adjust the level of assistance is addressed. The controller is conceived to tackle one of the main limitations when using electrical stimulation, i.e. the highly nonlinear and time-varying muscle response. An experimental procedure was conducted with healthy and post-stroke patients to corroborate the technical feasibility and the usability evaluation of the system. 3. The implementation of an associative strategy within the hybrid platform. Three different strategies based on electroencephalography and electromyography signals were analytically compared. The main idea is to provide a precise temporal association between the hybrid assistance delivered at the periphery (arm muscles) and the users’ own intention to move and to configure a feasible clinical setup to be use in real rehabilitation scenarios. 4. Carry out a comprehensive pilot clinical intervention considering a small cohort of patient with post-stroke patients to evaluate the different proposed concepts and assess the feasibility of using the hybrid system in rehabilitation settings. In summary, the works here presented prove the feasibility of using the hybrid robotic system as a rehabilitative tool with post-stroke subjects. Moreover, it is demonstrated the adaptive controller is able to adjust the level of assistance to achieve successful tracking movement with the affected arm. Remarkably, the accurate association in time between motor cortex activation, represented through the motor-related cortical potential measured with electroencephalography, and the supplied hybrid assistance during the execution of functional (multidegree of freedom) reaching movement facilitate distributed cortical plasticity. These results encourage the validation of the overall hybrid concept in a large clinical trial including an increased number of patients with a control group, in order to achieve more robust clinical results and confirm the presented herein.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Ramón Ceres Ruiz.- Secretario: Luis Enrique Moreno Lorente.- Vocal: Antonio Olivier

    Development of a hybrid assist-as-need hand exoskeleton for stroke rehabilitation.

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    Stroke is one of the leading causes of disability globally and can significantly impair a patient’s ability to function on a daily basis. Through physical rehabilitative measures a patient may regain a level of functional independence. However, required therapy dosages are often not met. Rehabilitation is typically implemented through manual one-to-one assistance with a physiotherapist, which quickly becomes labour intensive and costly. Hybrid application of functional electrical stimulation (FES) and robotic support can access the physiological benefits of direct muscle activation while providing controlled and repeatable motion assistance. Furthermore, patient engagement can be heightened through the integration of a volitional intent measure, such as electromyography (EMG). Current hybrid hand-exoskeletons have demonstrated that a balanced hybrid support profile can alleviate FES intensity and motor torque requirements, whilst improving reference tracking errors. However, these support profiles remain fixed and patient fatigue is not addressed. The aim of this thesis was to develop a proof-of-concept assist-as-need hybrid exoskeleton for post-stroke hand rehabilitation, with fatigue monitoring to guide the balance of support modalities. The device required the development and integration of a constant current (CC) stimulator, stimulus-resistant EMG device, and hand-exoskeleton. The hand exoskeleton in this work was formed from a parametric Watt I linkage model that adapts to different finger sizes. Each linkage was optimised with respect to angular precision and compactness using Differential Evolution (DE). The exoskeleton’s output trajectory was shown to be sensitive to parameter variation, potentially caused by finger measurement error and shifts in coupler placement. However, in a set of cylindrical grasping trials it was observed that a range of movement strategies could be employed towards a successful grasp. As there are many possible trajectories that result in a successful grasp, it was deduced that the exoskeleton can still provide functional assistance despite its sensitivity to parameter variation. The CC stimulator developed in this work has a part cost of USD 145andallowsflexibleadjustmentofwaveformparametersthroughanonboardmicrocontroller.Thedeviceisdesignedtooutputcurrentupto±30mAgivenavoltagecomplianceof±50V.Whenappliedacrossa2kload,thedeviceexhibitedalinearoutputtransferfunction,withamaximumramptrackingerrorof5ThestimulusresistantEMGdevicebuildsoncurrentdesignsbyusinganovelSchmitttriggerbasedartefactdetectionchanneltoadaptivelyblankstimulationartefactswithoutstimulatorsynchronisation.ThedesignhasapartcostofUSD145 and allows flexible adjustment of waveform parameters through an on-board micro-controller. The device is designed to output current up to ±30mA given a voltage compliance of ±50V. When applied across a 2kΩ load, the device exhibited a linear output transfer function, with a maximum ramp tracking error of 5%. The stimulus-resistant EMG device builds on current designs by using a novel Schmitt trigger based artefact detection channel to adaptively blank stimulation artefacts without stimulator synchronisation. The design has a part cost of USD 150 and has been made open-source. The device demonstrated its ability to record EMG over its predominant energy spectrum during stimulation, through the stimulation electrodes or through separate electrodes. Pearson’s correlation coefficients greater than 0.84 were identified be- tween the normalised spectra of volitional EMG (vEMG) estimates during stimulation and of stimulation-free EMG recordings. This spectral similarity permits future research into applications such as spectral-based monitoring of fatigue and muscle coherence, posing an advantage over current same-electrode stimulation and recording systems, which can- not sample the lower end of the EMG spectrum due to elevated high-pass filter cut-off frequencies. The stimulus-resistant EMG device was used to investigate elicited EMG (eEMG)-based fatigue metrics during vEMG-controlled stimulation and hybrid support profiles. During intermittent vEMG-controlled stimulation, the eEMG peak-to-peak amplitude (PTP) index was the median frequency (MDF) had a negative correlation for all subjects with R > 0:62 during stimulation-induced wrist flexion and R > 0:55 during stimulation-induced finger flexion. During hybrid FES-robotic support trials, a 40% reduction in stimulus intensity resulted in an average 21% reduction in MDF gradient magnitudes. This reflects lower levels of fatigue during the hybrid support profile and indicates that the MDF gradient can provide useful information on the progression of muscle fatigue. A hybrid exoskeleton system was formed through the integration of the CC stimulator, stimulus-resistant EMG device, and the hand exoskeleton developed in this work. The system provided assist-as-need functional grasp assistance through stimulation and robotic components, governed by the user’s vEMG. The hybrid support profile demonstrated consistent motion assistance with lowered stimulation intensities, which in-turn lowered the subjects’ perceived levels of fatigue

    Iterative Learning Control in Health Care: Electrical Stimulation and Robotic-Assisted Upper-Limb Stroke Rehabilitation

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    Usability engineering in the design and evaluation of a functional electrical stimulation system for upper limb rehabilitation

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    Chronic physical impairment of the hemiplegic upper limb (UL) is seen in an estimated 50-70% of stroke patients, who place a high priority on regaining upper limb function. Current therapy is insufficiently intensive, often not task-oriented and hence poorly aligned with the evidence base. Functional electrical stimulation (FES) has the potential to not only increase the intensity of task-focused therapy, but also provide certain unique features, notably direct excitation of lower motor neurons. However, current FES systems are limited in their functionality and/or difficult to use. Systems are also poorly aligned to therapists’ ways of working and uptake remains limited. To address these problems, a novel FES technology (UL FES Rehab Tool) has been developed. The control system design is reported in Sun, (2014). The aims of my thesis were to: 1) design a Graphical User Interface (GUI) that would enable therapists to quickly and easily set up an individually tailored library of FES tasks for each patient; 2) evaluate the usability and functionality of the UL FES Rehab Tool(software and hardware) in both laboratory (lab) and clinical settings. An iterative, mixed methods, five-phase usability engineering approach was used to design and evaluate the UL FES Rehab Tool. Phases one to three incorporated identification of therapists’ requirements, a user ‘assisted walkthrough’ of the software with expert and novice FES users and ‘rapid prototyping’ of the full system, using healthy participants. Further usability testing of the software & hardware was conducted in phase four with 1 physiotherapist and 6 patients, (total of 24 visits), in the chronic stage post-stroke. The work demonstrated in detail, for the first time, the impact of therapist involvement in the design of novel rehabilitation technology. To address therapists’ focus on setup time, using the phase four data set, a novel model to predict setup time was devised. This model was able to explain 51% of the variance in setup time based on two parameters, task complexity and patient impairment. Finally, in phase five, a summative usability evaluation of the final prototype was carried out in 2 sub-acute stroke units. Four therapists and 1 rehabilitation assistant used the UL FES Rehab Tool with 6 patients in the acute stage post-stroke. The UL FES Rehab Tool enabled all therapists and one therapy assistant to effectively deliver FES assisted upper limb task-oriented therapy to a range of stroke patients (Fugl-Meyer scores 8–65). The usability methods effectively captured objective and subjective feedback from therapists and patients. However the previous setup time model was unable to predict setup time, suggesting other factors were important in a clinical setting. Although participant numbers were low, the results suggested therapists’ predisposition to using technology and post-training confidence in using the technology may influence their willingness to engage with novel rehabilitation technologies. This study is the first to describe in detail the impact of a usability engineering approach on the design of a complex upper limb rehabilitation technology from early stage design to clinical evaluation. These methods can be generalised to other studies seeking to explore the usability of new forms of rehabilitation technologies

    Control and assessment of transhumeral prosthetic system

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    A neuroprothesis for tremor management

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    Tremor is the most common movement disorder, affecting ∼ 15 % of people over 50 years old according to some estimates. It appears due to a number of syndromes, being essential tremor and Parkinson's disease the most prevalent among them. None of these conditions is fully understood. Tremor is currently treated through drugs or neurosurgery, but unfortunately, it is not managed effectively in ∼25 % of the patients. Therefore, it constitutes a major cause of loss of independence and quality of life. Various alternative approaches for tremor management are reported in the literature. Among them, those devices that rely on the application of forces to the tremulous segments show a considerable potential. A number of prototypes that exploit this principle are available, spanning fixed devices and orthoses. However, none of them has fulfilled user's expectation for continuous use during daily living. This thesis presents the development and validation of a neuroprosthesis for tremor management. A neuroprosthesis is a system that restores or compensates for a neurological function that is lost. In this case, the neuroprosthesis aims at compensating the functional disability caused by the tremor. To this end, it applies forces to the tremulous limb through the control of muscle contraction, which is modulated according to the characteristics of the tremor. The concept design envisions the device as a textile that is worn on the affected limb, thus meeting the usability requirements defined by the patients. The development of the neuroprosthesis comprised the following tasks: 1. The development of a concept design of the neuroprosthesis, which incorporates state of the art knowledge on tremor, and user's needs. 2. The design and validation of a cognitive interface that parameterizes the tremor in functional contexts. This interface provides the information that the neuroprosthesis uses for tremor suppression. Two versions are developed: a multimodal interface that integrates the recordings of the whole neuromusculoskeletal system, and an interface incorporating only wearable movement sensors. The latter is intended for the functional validation of the neuroprosthesis, while the former is a proof of concept of an optimal interface for this type of applications. 3. The development of a novel approach for tremor suppression through transcutaneous neurostimulation. The approach relies on the modulation of muscle cocontraction as a means of attenuating the tremor without the need of conventional actuators. The experimental validation here provided demonstrates the feasibility and interest of the approach. In parallel with the validation of the neuroprosthesis, I performed a detailed study on the physiology of motoneurons in tremor, given the lack of a complete description of its behavior. The outcome of this study contributes to the interpretation of the results obtained with the neuroprosthesis, and opens new research lines, both related to alternative interventions and basic neuroscience. In summary, the results here presented demonstrate that tremor may be accurately parameterized while the patient performs functional activities, and that this information may be exploited to drive a neuroprosthesis for tremor management. Furthermore, the novel approach for tremor suppression presented in this dissertation constitutes a potential approach for treating upper limb tremor, either alone, or as a complement to pharmacotherapy. These results encourage the validation of the neuroprosthesis in a large cohort of patients, in order to enable its translation to the market. -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------El temblor es el trastorno del movimiento más común, afectando, según algunas estimaciones, al ∼15 % de la población de más de 50 años. Existen diversos "síndromes" que causan temblor, siendo el temblor esencial y la enfermedad de Parkinson los que presentan mayor prevalencia. Además, cabe resaltar que no existe una descripción completa de ninguno de ellos. En la actualidad el temblor se trata mediante una serie de fármacos o neurocirugía. A pesar de ello, el ∼ 25 % de los pacientes sufren problemas funcionales debido a su condición. Por tanto, es evidente que el temblor constituye una de las principales causas de dependencia y pérdida de calidad de vida. Realizando una revisión de las publicaciones científicas sobre el temblor, se observa que se ha propuesto un considerable número de tratamientos alternativos. Entre ellos destacan los dispositivos que se fundamentan en la aplicación de fuerzas sobre los segmentos afectados por el temblor, de los que ya se ha evaluado una serie de prototipos. Estos abarcan desde dispositivos fijados a otras estructuras hasta ortesis. Sin embargo, ninguno de ellos satisface las expectativas de los usuarios para su uso durante el día a día. Esta tesis presenta el diseño y validación de una neruoprótesis para el tratamiento del temblor. Una neuroprótesis es un sistema que reemplaza o compensa una función neurológica perdida. En este caso, la neuroprótesis tiene como objetivo compensar la discapacidad motora causada por el temblor. Para ello aplica fuerzas al miembro afectado a través del control del nivel de contracción muscular, que se modula según las características del temblor. El diseño conceptual contempla al dispositivo como un textil que se viste en el brazo afectado, satisfaciendo los requisitos de usabilidad definidos por los pacientes. El desarrollo de la neuroprótesis abarcó las siguientes tareas: 1. El desarrollo del diseño conceptual de la neuroprótesis, que incorpora el conocimiento actual sobre el temblor, y las necesidades de los usuarios. 2. El diseño y validación de una interfaz cognitiva que parametriza el temblor durante tareas funcionales. La información obtenida con esta interfaz es usada por la neuroprótesis para modular la corriente aplicada mediante técnicas de neuroestimulación. Se desarrollan dos versiones de la interfaz cognitiva: una interfaz multimodal que integra información de todo el sistema neuromusculoesquelético, y una interfaz que implementa únicamente sensores vestibles de movimiento. La segunda interfaz fue la que se usó durante la validación funcional de la neuroprótesis, mientras que la primera es una prueba de concepto de una interfaz óptima para este tipo de aplicaciones. 3. El desarrollo de una nueva aproximación para la supresión del temblor mediante neuroestimulación transcutánea. Dicha aproximación se fundamenta en la modulación del grado de co-contracción de los músculos afectados como forma de atenuar el temblor, sin necesidad de usar actuadores convencionales. La evaluación experimental sirvió para demostrar la viabilidad e interés de la intervención. En paralelo a la validación de la neuroprótesis, llevé a cabo un estudio detallado de la fisiología de las motoneuronas en el caso del temblor, dado que no existe una descripción del funcionamiento de las mismas en el caso de este trastorno. Este estudio sirve para ayudar a la interpretación de los resultados de la neuroprótesis, y para abrir una serie de líneas futuras de investigación, tanto sobre nuevas intervenciones para el temblor, como sobre neurociencia básica. En resumen, los resultados que se presentan en esta tesis demuestran que es posible parametrizar de una forma precisa el temblor durante la realización de tareas funcionales, y que esta información sirve para controlar una neuroprótesis para el tratamiento del temblor. Además, la nueva aproximación para la compensación del temblor que se presenta tiene el potencial de convertirse en un tratamiento alternativo para el temblor de miembro superior, ya sea de forma independiente o como complemento a los fármacos. Estos resultados alientan la validación de la neuroprótesis en una cohorte grande de pacientes, con el objetivo de facilitar su transferencia al mercado

    EOG-Based Human–Computer Interface: 2000–2020 Review

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    Electro-oculography (EOG)-based brain-computer interface (BCI) is a relevant technology influencing physical medicine, daily life, gaming and even the aeronautics field. EOG-based BCI systems record activity related to users' intention, perception and motor decisions. It converts the bio-physiological signals into commands for external hardware, and it executes the operation expected by the user through the output device. EOG signal is used for identifying and classifying eye movements through active or passive interaction. Both types of interaction have the potential for controlling the output device by performing the user's communication with the environment. In the aeronautical field, investigations of EOG-BCI systems are being explored as a relevant tool to replace the manual command and as a communicative tool dedicated to accelerating the user's intention. This paper reviews the last two decades of EOG-based BCI studies and provides a structured design space with a large set of representative papers. Our purpose is to introduce the existing BCI systems based on EOG signals and to inspire the design of new ones. First, we highlight the basic components of EOG-based BCI studies, including EOG signal acquisition, EOG device particularity, extracted features, translation algorithms, and interaction commands. Second, we provide an overview of EOG-based BCI applications in the real and virtual environment along with the aeronautical application. We conclude with a discussion of the actual limits of EOG devices regarding existing systems. Finally, we provide suggestions to gain insight for future design inquiries
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