Adaptive walking assistance based on human-orthosis interaction

An assistive rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy monitors the human-orthosis interaction torques and modifies the orthosis operation mode depending on its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints stiffness in function of these interaction torques and to the deviation from the desired trajectory. A walking pattern, an average of recorded gaits, is used as reference input. The human-orthosis interaction torques are used to define the time instant when robot assistance is needed and its degree. The objective of this work is to demonstrate the feasibility of ensuring a dynamic stability by means of an efficient real-time stiffness adaptation for multiple joints and simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from Spinal cord injury and Stroke.Peer ReviewedPostprint (author's final draft

Assist-as-needed impedance control strategy for a wearable ankle robotic orthosis

The use of robots in rehabilitation attempts an effective, compliant, and time-efficient gait recovery while adapting the assistance to the user's needs. Assist-as-needed strategies (AAN), such as adaptive impedance control, have been reported as prominent strategies to enable this recovery effects. This study proposes an interaction-based assist-as-needed impedance control strategy for an ankle robotic orthosis that adapts the robotic assistance by changing the Human-Robot interaction stiffness. The adaptability of the interaction stiffness allows the real-time passage from passive assistance to an active one, approaching AAN gait training. The interaction stiffness was successfully estimated by linear regression of the Human-Robot interaction torque vs angle trajectory curve. From the validation with seven able-bodied subjects, we verified the suitability of this adaptive impedance control for a more compliant, natural, and comfortable motion than the trajectory tracking control. Moreover, the proposed strategy considers the users' motion intention and encourages them to interact closely with the robotic device while guiding their ankle trajectory according to desired trajectories. These achievements contribute to AAN gait training.This work has been supported by the FEDER Funds through the Programa Operacional Regional do Norte and national funds from Fundação para a Ciência e Tecnologia with the project SmartOs under Grant NORTE-01-0145-FEDER-030386, and through the COMPETE 2020—Programa Operacional Competitividade e Internacionalização (POCI)—with the Reference Project under Grant POCI-01-0145-FEDER-006941

An Active Exoskeleton Called P.I.G.R.O. Designed for Unloaded Robotic Neurorehabilitation Training

The development of innovative robotic devices allows the design of exoskeletons for robotic neurorehabilitation training. This paper presents the active exoskeleton called pneumatic interactive gait rehabilitation orthosis (P.I.G.R.O.), developed by the authors. The main innovative characteristic of this prototype is its design for fully unloaded robotic neurorehabilitation training, specific for brain-injured patients. It has six degrees of freedom (DOF) in the sagittal plane, an active ankle joint (removable if it is required); a wide range of anthropometric regulations, both for men and for women; a useful human machine interface (HMI); and an innovative harness system for the patient for the unloaded training. It is realized using light and strong materials, and it is electropneumatically controlled. In particular the authors also studied and defined some innovative input control curves useful for the unloaded training. In this paper, the main characteristics and innovations of P.I.G.R.O. are presented

Control of an ambulatory exoskeleton with a brain-machine interface for spinal cord injury gait rehabilitation

The closed-loop control of rehabilitative technologies by neural commands has shown a great potential to improve motor recovery in patients suffering from paralysis. Brain-machine interfaces (BMI) can be used as a natural control method for such technologies. BMI provides a continuous association between the brain activity and peripheral stimulation, with the potential to induce plastic changes in the nervous system. Paraplegic patients, and especially the ones with incomplete injuries, constitute a potential target population to be rehabilitated with brain-controlled robotic systems, as they may improve their gait function after the reinforcement of their spared intact neural pathways. This paper proposes a closed-loop BMI system to control an ambulatory exoskeleton-without any weight or balance support-for gait rehabilitation of incomplete spinal cord injury (SCI) patients. The integrated system was validated with three healthy subjects, and its viability in a clinical scenario was tested with four SCI patients. Using a cue-guided paradigm, the electroencephalographic signals of the subjects were used to decode their gait intention and to trigger the movements of the exoskeleton. We designed a protocol with a special emphasis on safety, as patients with poor balance were required to stand and walk. We continuously monitored their fatigue and exertion level, and conducted usability and user-satisfaction tests after the experiments. The results show that, for the three healthy subjects, 84.44 ± 14.56% of the trials were correctly decoded. Three out of four patients performed at least one successful BMI session, with an average performance of 77.6 1 ± 14.72%. The shared control strategy implemented (i.e., the exoskeleton could only move during specific periods of time) was effective in preventing unexpected movements during periods in which patients were asked to relax. On average, 55.22 ± 16.69% and 40.45 ± 16.98% of the trials (for healthy subjects and patients, respectively) would have suffered from unexpected activations (i.e., false positives) without the proposed control strategy. All the patients showed low exertion and fatigue levels during the performance of the experiments. This paper constitutes a proof-of-concept study to validate the feasibility of a BMI to control an ambulatory exoskeleton by patients with incomplete paraplegia (i.e., patients with good prognosis for gait rehabilitation)

Adaptive control for wearable robots in human-centered rehabilitation tasks

Robotic rehabilitation therapies have been improving by providing the needed assistance to the patient, in a human-centered environment, and also helping the therapist to choose the necessary procedure. This thesis presents an adaptive "Assistance-as-needed" strategy which adheres to the specific needs of the patient and with the inputs from the therapist, whenever needed. The exertion of assistive and responsive behavior of the lower limb wearable robot is dedicated for the rehabilitation of incomplete spinal cord injury (SCI) patients. The main objective is to propose and evaluate an adaptive control model on a wearable robot, assisting the user and adhering to their needs, with no or less combination of external devices. The adaptation must be more interactive to understand the user needs and their volitional orders. Similarly, by using the existing muscular strength, in incomplete SCI patients, as a motivation to pursue the movement and assist them, only when needed. The adaptive behavior of the wearable robot is proposed by monitoring the interaction and movement of the user. This adaptation is achieved by modulating the stiffness of the exoskeleton in function of joint parameters, such as positions and interaction torques. These joint parameters are measured from the user independently and then used to update the new stiffness value. The adaptive algorithm performs with no need of external sensors, making it simple in terms of usage. In terms of rehabilitation, it is also desirable to be compatible with combination of assistive devices such as muscle stimulation, neural activity (BMI) and body balance (Wii), to deliver a user friendly and effective therapy. Combination of two control approaches has been employed, to improve the efficiency of the adaptive control model and was evaluated using a wearable lower limb exoskeleton device, H1. The control approaches, Hierarchical and Task based approach have been used to assist the patient as needed and simultaneously motivate the patient to pursue the therapy. Hierarchical approach facilitates combination of multiple devices to deliver an effective therapy by categorizing the control architecture in two layers, Low level and High level control. Task-based approaches engage in each task individually and allow the possibility to combine them at any point of time. It is also necessary to provide an interaction based approach to ensure the complete involvement of the user and for an effective therapy. By means of this dissertation, a task based adaptive control is proposed, in function of human-orthosis interaction, which is applied on a hierarchical control scheme. This control scheme is employed in a wearable robot, with the intention to be applied or accommodated to different pathologies, with its adaptive capabilities. The adaptive control model for gait assistance provides a comprehensive solution through a single implementation: Adaptation inside a gait cycle, continuous support through gait training and in real time. The performance of this control model has been evaluated with healthy subjects, as a preliminary study, and with paraplegic patients. Results of the healthy subjects showed a significant change in the pattern of the interaction torques, elucidating a change in the effort and adaptation to the user movement. In case of patients, the adaptation showed a significant improvement in the joint performance (flexion/extension range) and change in interaction torques. The change in interaction torques (positive to negative) reflects the active participation of the patient, which also explained the adaptive performance. The patients also reported that the movement of the exoskeleton is flexible and the walking patterns were similar to their own distinct patterns. The presented work is performed as part of the project HYPER, funded by Ministerio de Ciencia y Innovación, Spain. (CSD2009 - 00067 CONSOLIDER INGENIOLas terapias de rehabilitación robóticas han sido mejoradas gracias a la inclusión de la asistencia bajo demanda, adaptada a las variaciones de las necesidades del paciente, así como a la inclusión de la ayuda al terapeuta en la elección del procedimiento necesario. Esta tesis presenta una estrategia adaptativa de asistencia bajo demanda, la cual se ajusta a las necesidades específicas del paciente junto a las aportaciones del terapeuta siempre que sea necesario. El esfuerzo del comportamiento asistencial y receptivo del robot personal portátil para extremidades inferiores está dedicado a la rehabilitación de pacientes con lesión de la médula espinal (LME) incompleta. El objetivo principal es proponer y evaluar un modelo de control adaptativo en un robot portátil, ayudando al usuario y cumpliendo con sus necesidades, en ausencia o con reducción de dispositivos externos. La adaptación debe ser más interactiva para entender las necesidades del usuario y sus intenciones u órdenes volitivas. De modo similar, usando la fuerza muscular existente (en pacientes con LME incompleta) como motivación para lograr el movimiento y asistirles solo cuando sea necesario. El comportamiento adaptativo del robot portátil se propone mediante la monitorización de la interacción y movimiento del usuario. Esta adaptación conjunta se consigue modulando la rigidez en función de los parámetros de la articulación, tales como posiciones y pares de torsión. Dichos parámetros se miden del usuario de forma independiente y posteriormente se usan para actualizar el nuevo valor de la rigidez. El desempeño del algoritmo adaptativo no requiere de sensores externos, lo que favorece la simplicidad de su uso. Para una adecuada rehabilitación, efectiva y accesible para el usuario, es necesaria la compatibilidad con diversos mecanismos de asistencia tales como estimulación muscular, actividad neuronal y equilibrio corporal. Para mejorar la eficiencia del modelo de control adaptativo se ha empleado una combinación de dos enfoques de control, y para su evaluación se ha utilizado un exoesqueleto robótico H1. Los enfoques de control Jerárquico y de Tarea se han utilizado para ayudar al usuario según sea necesario, y al mismo tiempo motivarle para continuar el tratamiento. Enfoque jerárquico facilita la combinación de múltiples dispositivos para ofrecer un tratamiento eficaz mediante la categorización de la arquitectura de control en dos niveles : el control de bajo nivel y de alto nivel. Los enfoques basados en tareas involucran a la persona en cada tarea individual, y ofrecen la posibilidad de combinarlas en cualquier momento. También es necesario proporcionar un enfoque basado en la interacción con el usuario, para asegurar su participación y lograr así una terapia eficaz. Mediante esta tesis, proponemos un control adaptativo basado en tareas y en función de la interacción persona-ortesis, que se aplica en un esquema de control jerárquico. Este esquema de control se emplea en un robot portátil, con la intención de ser aplicado o acomodado a diferentes patologías, con sus capacidades de adaptación. El modelo de control adaptativo propuesto proporciona una solución integral a través de una única aplicación: adaptación dentro de la marcha y apoyo continúo a través de ejercicios de movilidad en tiempo real. El rendimiento del modelo se ha evaluado en sujetos sanos según un estudio preliminar, y posteriormente también en pacientes parapléjicos. Los resultados en sujetos sanos mostraron un cambio significativo en el patrón de los pares de interacción, elucidando un cambio en la energía y la adaptación al movimiento del usuario. En el caso de los pacientes, la adaptación mostró una mejora significativa en la actuación conjunta (rango de flexión / extensión) y el cambio en pares de interacción. El cambio activo en pares de interacción (positivo a negativo) refleja la participación activa del paciente, lo que también explica el comportamiento adaptativo

Adaptive walking assistance based on human-orthosis interaction

An assistive rehabilitation strategy for a lower-limb wearable robot is proposed and evaluated. The control strategy monitors the human-orthosis interaction torques and modifies the orthosis operation mode depending on its evolution with respect to a normal gait pattern. The control algorithm relies on the adaptation of the joints stiffness in function of these interaction torques and to the deviation from the desired trajectory. A walking pattern, an average of recorded gaits, is used as reference input. The human-orthosis interaction torques are used to define the time instant when robot assistance is needed and its degree. The objective of this work is to demonstrate the feasibility of ensuring a dynamic stability by means of an efficient real-time stiffness adaptation for multiple joints and simultaneously maintaining their synchronization. The algorithm has been tested with five healthy subjects showing its efficient behavior in maintaining the equilibrium while walking in presence of external forces. The work is performed as a preliminary study to assist patients suffering from Spinal cord injury and Stroke.Peer Reviewe