Robotic exoskeleton with an assist-as-needed control strategy for gait rehabilitation after stroke

Stroke is a loss of brain function caused by a disturbance on the blood supply to the brain. The main consequence of a stroke is a serious long-term disability, and it affects millions of people around the world every year. Motor recovery after stroke is primarily based on physical therapy and the most common rehabilitation method focuses on the task specific approach. Gait is one of the most important daily life activity affected in stroke victims, leading to poor ambulatory activity. Therefore, much effort has been devoted to improve gait rehabilitation. Traditional gait therapy is mostly based on treadmill training, with patient’s body weight partially supported by a harness system. Physical therapists need to manually assist patients in the correct way to move their legs. However, this technique is usually very exhausting for therapists and, as a result, the training duration is limited by the physical conditions of the therapists themselves. Moreover, multiple therapists are required to assist a single patient on both legs, and it is very difficult to coordinate and properly control the body segments of interest. In order to help physical therapists to improve the rehabilitation process, robotic exoskeletons can come into play. Robotics exoskeletons consist of mechatronic structures attached to subject’s limbs in order to assist or enhance movements. These robotic devices have emerged as a promising approach to restore gait and improve motor function of impaired stroke victims, by applying intensive and repetitive training. However, active subject participation during the therapy is paramount to many of the potential recovery pathways and, therefore, it is an important feature of the gait training. To this end, robotics devices should not impose fixed limb trajectories while patient remains passive. These have been the main motivations for the research of this dissertation. The overall aim was to generate the necessary knowledge to design, develop and validate a novel lower limb robotic exoskeleton and an assist-as-needed therapy for gait rehabilitation in post-stroke patients. Research activities were conducted towards the development of the hardware and the control methods required to prove the concept with a clinical evaluation. The first part of the research was dedicated to design and implement a lightweight robotic exoskeleton with a comfortable embodiment to the user. It was envisioned as a completely actuated device in the sagittal plane, capable of providing the necessary torque to move the hip, knee and ankle joints through the walking process. The device, that does not extend above mid-abdomen and requires nothing to be worn over the shoulders or above the lower back, presumably renders more comfort to the user. Furthermore, the robotic exoskeleton is an autonomous device capable of overground walking, aiming to motivate and engage patients by performing gait rehabilitation in a real environment. The second research part was devoted to implement a control approach that assist the patient only when needed. This method creates a force field that guides patient’s limb in a correct trajectory. In this way, the robotic exoskeleton only applies forces when the patient deviates from the trajectory. The force field provides haptic feedback that is processed by the patient, thus leading to a continuous improvement of the motor functions. Finally, research was conducted to evaluate the robotic exoskeleton and its control approach in a clinical study with post-stroke patients. This study aimed to be a proof-of-concept of all design and implementation applied to a real clinical rehabilitation scenario. Several aspects were evaluated: the robotic exoskeleton control performance, patients’ attitudes and motivation towards the use of the device, patients’ safety and tolerance to the intensive robotic training and the impact of the robotic training on the walking function of the patients. Results have shown that the device is safe, easy to use and have positive impact on walking functions. The patients tolerated the walking therapy very well and were motivated by training with the device. These results motivate further research on overground walking therapy for stroke rehabilitation with the robotic exoskeleton. The work presented in this dissertation comprises all the way from the research to implementation and evaluation of a final device. The technology resulting from the work presented here has been transferred to a spin-o↵ company, which is now commercializing the device in different countries as a research tool to be used in clinical studies.Un accidente cerebrovascular es una pérdida de la función cerebral causada por una perturbación en el suministro sanguíneo al cerebro. La principal consecuencia de esta enfermedad es una grave discapacidad a largo plazo, que afecta a millones de personas en todo el mundo a cada año. La recuperación motora después de un accidente cerebrovascular se basa principalmente en la terapia física, y el método de rehabilitación más frecuente se centra en un entrenamiento específico. La marcha es una de las más importantes actividades de la vida diaria afectada por un accidente cerebrovascular, conduciendo a una capacidad ambulatoria deficiente. Debido a eso, mucho esfuerzo se ha dedicado a la rehabilitación de la marcha. La terapia tradicional de la marcha se basa principalmente en el entrenamiento en cinta rodante, con descarga de peso parcial usando un sistema de arnés. Los fisioterapeutas ayudan manualmente a los pacientes a mover sus piernas en la forma correcta. Sin embargo, esta técnica suele ser muy extenuante para los terapeutas, limitando la duración de la terapia por las condiciones físicas de estos. Además, se requieren múltiples terapeutas para asistir a un solo paciente en ambas piernas, siendo muy difícil de coordinar y controlar adecuadamente los segmentos corporales de interés. Con el fin de ayudar a los terapeutas físicos a mejorar el proceso de rehabilitación, los exosqueletos robóticos pueden ser muy útiles. Los exoesqueletos robóticos consisten en estructuras mecatrónicas conectadas a las extremidades del usuario, con el fin de asistir sus movimientos. Estos dispositivos robóticos han surgido como una forma prometedora de restaurar la marcha y mejorar la función motora en víctimas de accidentes cerebrovasculares, aplicando un entrenamiento intensivo y repetitivo. Sin embargo, la participación activa del paciente en la terapia es primordial para muchas de las posibles vías de recuperación y, por lo tanto, es una característica importante del entrenamiento de la marcha. Para este fin, los dispositivos robóticos no deben imponer trayectorias fijas en las extremidades del paciente mientras este permanece pasivo. Estos desafíos en los procesos de rehabilitación han sido la principal motivación para la investigación en esta tesis doctoral. El objetivo principal es generar los conocimientos necesarios para diseñar, desarrollar y validar un exoesqueleto robótico y una terapia de asistencia bajo demanda para la rehabilitación de la marcha en pacientes tras un accidente cerebrovascular. Actividades de investigación fueron llevadas a cabo para el desarrollo del hardware y de los métodos de control necesarios para una prueba de concepto mediante una evaluación clínica. La primera parte de la investigación fue dedicada a diseñar e implementar un exoesqueleto robótico ligero y cómodo para el usuario. Fue concebido un dispositivo completamente actuado en el plano sagital, capaz de proporcionar el par necesario para mover las articulaciones de la cadera, rodilla y tobillo durante la marcha. El dispositivo no se extiende por encima de mitad del abdomen y no requiere llevar nada sobre los hombros o en el tronco, proporcionando más comodidad al usuario. Además, el exoesqueleto robótico es un dispositivo autónomo capaz de asistir marcha ambulatoria, con el objetivo de motivar a los pacientes por medio de rehabilitación en un entorno real. La segunda parte de la investigación fue dedicada a implementar una estrategia de control para ayudar al paciente bajo demanda. El método crea un campo de fuerzas que guía la extremidad del paciente en la trayectoria correcta. De esta manera, el exoesqueleto robótico sólo aplica fuerzas cuando el paciente se desvía de la trayectoria. El campo de fuerza proporciona retroalimentación háptica que es procesada por el paciente, lo que conduce a una mejora continua de las funciones motoras. Por último, fue llevada a cabo una investigación para evaluar el exoesqueleto robótico y su estrategia de control en un estudio clínico con pacientes que han sufrido un accidente cerebrovascular. Este estudio fue una prueba de concepto del diseño y de la implementación del dispositivo aplicada a un escenario de rehabilitación clínica real. Se evaluaron varios aspectos: el desempeño de la estrategia de control, las actitudes y motivación de los pacientes hacia el uso del dispositivo, la seguridad del paciente y su tolerancia a la terapia robótica intensiva y el impacto de la rehabilitación en la marcha de los pacientes. Los resultados han demostrado que el dispositivo es seguro, fácil de usar y tiene un impacto positivo en la marcha. Los pacientes toleraron la terapia robótica muy bien y estuvieron motivados por el entrenamiento con el dispositivo. Estos resultados motivan a seguir la investigación con el exoesqueleto robótico aplicado a la rehabilitación de marcha en pacientes que han sufrido un accidente cerebrovascular. El trabajo presentado en esta tesis doctoral comprende todo el camino desde la investigación hasta la ejecución y evaluación de un dispositivo terminado. La tecnología resultante del trabajo que aquí se presenta ha sido transferida a una empresa spin-off, que ahora está comercializando el dispositivo en diferentes países como una herramienta de investigación para ser utilizada en estudios clínicos.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Luís Enrique Moreno Lorente.-Secretario: Juan Aranda López.-Vocal: Jose María Azorín Poved

Design and control of a robotic exoskeleton form gait rehabilitation

Tesis de Máster escrita para la obtención del Título de Grado en el Official Master in Robotics and Automation. Universidad Carlos III de Madrid. xxiii, 71 p. : il., diagr.Fecha de defensa de la tesis de máster: septiembre del 2013.Exoskeletons are becoming a very powerful tool to help therapists in the rehabilitation of patients who have suffered from neurological conditions, in particular stroke or spinal cord injury. This work presents a robotic exoskeleton designed to assist overground gait training for patients with deficits in gait coordination. The device is a bilateral exoskeleton with six degrees of freedom. It is designed to implement different control strategies. An adaptive trajectory control has been developed to guide the patient’s limb within a desired path, allowing a deviation based on torque of interaction between the user and the exoskeleton. An admittance control strategy allows the robotic platform to capture the user’s movements during assistive training and to replicate them during active training. Experimental results show that the exoskeleton can adapt a pre-recorded gait pattern to the gait pattern of a specific user. Future investigations will evaluate the device in the rehabilitation of patients who have suffered from stroke. A comparative analysis of the effectiveness of different robotic therapies will be proposed.Peer reviewe

BMIs for Motor Rehabilitation: Key Concepts and Challenges

The most recent rehabilitation and diagnostics technologies, including robotics, neuroprostheses, brain-machine interfaces and electromyography systems

Inertial Sensor Error Reduction through Calibration and Sensor Fusion

This paper presents the comparison between cooperative and local Kalman Filters (KF) for estimating the absolute segment angle, under two calibration conditions. A simplified calibration, that can be replicated in most laboratories; and a complex calibration, similar to that applied by commercial vendors. The cooperative filters use information from either all inertial sensors attached to the body, Matricial KF; or use information from the inertial sensors and the potentiometers of an exoskeleton, Markovian KF. A one minute walking trial of a subject walking with a 6-DoF exoskeleton was used to assess the absolute segment angle of the trunk, thigh, shank, and foot. The results indicate that regardless of the segment and filter applied, the more complex calibration always results in a significantly better performance compared to the simplified calibration. The interaction between filter and calibration suggests that when the quality of the calibration is unknown the Markovian KF is recommended. Applying the complex calibration, the Matricial and Markovian KF perform similarly, with average RMSE below 1.22 degrees. Cooperative KFs perform better or at least equally good as Local KF, we therefore recommend to use cooperative KFs instead of local KFs for control or analysis of walking.We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).This work was supported by the HYPER project of the CONSOLIDER-INGENIO 2010 program of Spain, under grant CSD2009-00067; Fundação de Apoio à Pesquisa do Estado de São Paulo (FAPESP), under grant 2012/05552-9; The BIOMOT project within the Seventh Framework Programme for Research of the European Commission (611695); and by a grant from the Flemish agency for Innovation by Science and Technology (MIRAD, IWT-SBO 120057) We also thank Technaid S.L. for the use of the calibration equipment. We furthermore like to thank J.C. Moreno for his valuable contributions in writing this text

The H2 robotic exoskeleton for gait rehabilitation after stroke: early findings from a clinical study

[Background] Stroke significantly affects thousands of individuals annually, leading to considerable physical impairment and functional disability. Gait is one of the most important activities of daily living affected in stroke survivors. Recent technological developments in powered robotics exoskeletons can create powerful adjunctive tools for rehabilitation and potentially accelerate functional recovery. Here, we present the development and evaluation of a novel lower limb robotic exoskeleton, namely H2 (Technaid S.L., Spain), for gait rehabilitation in stroke survivors.[Methods] H2 has six actuated joints and is designed to allow intensive overground gait training. An assistive gait control algorithm was developed to create a force field along a desired trajectory, only applying torque when patients deviate from the prescribed movement pattern. The device was evaluated in 3 hemiparetic stroke patients across 4 weeks of training per individual (approximately 12 sessions). The study was approved by the Institutional Review Board at the University of Houston. The main objective of this initial pre-clinical study was to evaluate the safety and usability of the exoskeleton. A Likert scale was used to measure patient’s perception about the easy of use of the device.[Results] Three stroke patients completed the study. The training was well tolerated and no adverse events occurred. Early findings demonstrate that H2 appears to be safe and easy to use in the participants of this study. The overground training environment employed as a means to enhance active patient engagement proved to be challenging and exciting for patients. These results are promising and encourage future rehabilitation training with a larger cohort of patients.[Conclusions] The developed exoskeleton enables longitudinal overground training of walking in hemiparetic patients after stroke. The system is robust and safe when applied to assist a stroke patient performing an overground walking task. Such device opens the opportunity to study means to optimize a rehabilitation treatment that can be customized for individuals.[Trial registration] This study was registered at ClinicalTrials.gov (https://clinicaltrials.gov/show/NCT02114450).This work has been partially supported by the Noninvasive Brain-Machine Interface Lab at the University of Houston and the HYPER Project (Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders). Ministerio de Ciencia y Innovación, Spain (CSD2009 - 00067 CONSOLIDER INGENIO 2010).Peer reviewe

EMG-driven models of human-machine interaction in individuals wearing the H2 exoskeleton

© 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd.EMG-driven modeling has been mostly used offline and on powerful desktop computers, limiting the application of this technique to neurorehabilitation settings. In this paper, we demonstrate the use of EMG-driven modeling in online (i.e. in real-time) running on a fully portable embedded system and interfaced concurrently with a powered lower limb exoskeleton. This work provides evidence of the feasibility of real-time model-based control of complex multi-joint exoskeleton system, thus opening new avenues for personalised robot-aided rehabilitation interventions

Global Kalman filter approaches to estimate absolute angles of lower limb segments

[Background] In this paper we propose the use of global Kalman filters (KFs) to estimate absolute angles of lower limb segments. Standard approaches adopt KFs to improve the performance of inertial sensors based on individual link configurations. In consequence, for a multi-body system like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link angle estimations (e.g., foot). Global KF approaches, on the other hand, correlate the collective contribution of all signals from lower limb segments observed in the state-space model through the filtering process. We present a novel global KF (matricial global KF) relying only on inertial sensor data, and validate both this KF and a previously presented global KF (Markov Jump Linear Systems, MJLS-based KF), which fuses data from inertial sensors and encoders from an exoskeleton. We furthermore compare both methods to the commonly used local KF.[Results] The results indicate that the global KFs performed significantly better than the local KF, with an average root mean square error (RMSE) of respectively 0.942° for the MJLS-based KF, 1.167° for the matrical global KF, and 1.202° for the local KFs. Including the data from the exoskeleton encoders also resulted in a significant increase in performance.[Conclusion] The results indicate that the current practice of using KFs based on local models is suboptimal. Both the presented KF based on inertial sensor data, as well our previously presented global approach fusing inertial sensor data with data from exoskeleton encoders, were superior to local KFs. We therefore recommend to use global KFs for gait analysis and exoskeleton control.This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), under Grant 2012/05552–9; Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), under Grant 456089/2014–4; the HYPER project of the CONSOLIDER-INGENIO 2010 program of Spain, under Grant CSD2009–00067; the XoSoft project, Soft modular biomimetic exoskeleton to assist people with mobility impairments, contract H2020– ICT24–2016–688175; and by a grant from the Flemish agency for Innovation by Science and Technology (MIRAD, IWT–SBO 120057).Peer reviewe