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

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

Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable Hands-free Dynamic Walking

This manuscript presents control of a high-DOF fully actuated lower-limb exoskeleton for paraplegic individuals. The key novelty is the ability for the user to walk without the use of crutches or other external means of stabilization. We harness the power of modern optimization techniques and supervised machine learning to develop a smooth feedback control policy that provides robust velocity regulation and perturbation rejection. Preliminary evaluation of the stability and robustness of the proposed approach is demonstrated through the Gazebo simulation environment. In addition, preliminary experimental results with (complete) paraplegic individuals are included for the previous version of the controller.Comment: Submitted to IEEE Control System Magazine. This version addresses reviewers' concerns about the robustness of the algorithm and the motivation for using such exoskeleton

Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation

This paper introduces a newly developed gait rehabilitation device. The device, called LOPES, combines a freely translatable and 2-D-actuated pelvis segment with a leg exoskeleton containing three actuated rotational joints: two at the hip and one at the knee. The joints are impedance controlled to allow bidirectional mechanical interaction between the robot and the training subject. Evaluation measurements show that the device allows both a "pa- tient-in-charge" and "robot-in-charge" mode, in which the robot is controlled either to follow or to guide a patient, respectively. Electromyography (EMG) measurements (one subject) on eight important leg muscles, show that free walking in the device strongly resembles free treadmill walking; an indication that the device can offer task-specific gait training. The possibilities and limitations to using the device as gait measurement tool are also shown at the moment position measurements are not accurate enough for inverse-dynamical gait analysis

A Novel Design and Implementation of a 4-DOF Upper Limb Exoskeleton for Stroke Rehabilitation with Active Assistive Control Strategy

We developed a robot, CUREs (Chulalongkorn University Rehabilitation Robotic Exoskeleton system), for upper extremity rehabilitation. The active assistive control strategy based on the impedance force control is developed and implemented to obtain assistive-resistive paths tracking for rehabilitation activities. The desired trajectory or rehabilitated training pattern for each specific patient need to be assigned first by a medical doctor and a physical therapy. The therapist can program the desired trajectory by guiding the patient arm based on the assigned path pattern and the set of via points will be stored and used for generating the desired trajectory. The desired trajectory will be stored specific for the patient and can be called back anytime. During the rehabilitation, the robot can assist and resist the patient’s arm to follow the desired trajectory. If the patient has difficulty moving his arm to track the desired path, the robot will help by adding more torque to help the patient to move his arm to reduce the error between the desired path and the actual posture. And if the patient himself can move his arm tracking the desired path, the robot will not apply any more force to assist or resist. The necessary state variables such as angular position and torque can be recorded during the training. The main purpose of the experiment, follow the medical ethic, is to assure that there is no side effect for using this rehabilitation robot. Five subacute stroke patients participated in this pilot study. All patients have severe upper extremity weakness. The medical doctor will assign the training pattern based on patient condition. The result showed that the Fugl-Meyer Assessment Upper Extremity Scale was improved after 10 days of training in all participants without any sign of side effect.We developed a robot, CUREs (Chulalongkorn University Rehabilitation Robotic Exoskeleton system), for upper extremity rehabilitation. The active assistive control strategy based on the impedance force control is developed and implemented to obtain assistive-resistive paths tracking for rehabilitation activities. The desired trajectory or rehabilitated training pattern for each specific patient need to be assigned first by a medical doctor and a physical therapy. The therapist can program the desired trajectory by guiding the patient arm based on the assigned path pattern and the set of via points will be stored and used for generating the desired trajectory. The desired trajectory will be stored specific for the patient and can be called back anytime. During the rehabilitation, the robot can assist and resist the patient’s arm to follow the desired trajectory. If the patient has difficulty moving his arm to track the desired path, the robot will help by adding more torque to help the patient to move his arm to reduce the error between the desired path and the actual posture. And if the patient himself can move his arm tracking the desired path, the robot will not apply any more force to assist or resist. The necessary state variables such as angular position and torque can be recorded during the training. The main purpose of the experiment, follow the medical ethic, is to assure that there is no side effect for using this rehabilitation robot. Five subacute stroke patients participated in this pilot study. All patients have severe upper extremity weakness. The medical doctor will assign the training pattern based on patient condition. The result showed that the Fugl-Meyer Assessment Upper Extremity Scale was improved after 10 days of training in all participants without any sign of side effect

Adaptive Control of a Wearable Exoskeleton for Upper-Extremity Neurorehabilitation

The paper describes the implementation and testing of two adaptive controllers developed for a wearable, underactuated upper extremity therapy robot – RUPERT (Robotic Upper Extremity Repetitive Trainer). The controllers developed in this study were used to implement two adaptive robotic therapy modes – the adaptive co-operative mode and the adaptive active-assist mode – that are based on two different approaches for providing robotic assistance for task practice. The adaptive active-assist mode completes therapy tasks when a subject is unable to do so voluntarily. This robotic therapy mode is a novel implementation of the idea of an active-assist therapy mode; it utilizes the measure of a subject’s motor ability, along with their real-time movement kinematics to initiate robotic assistance at the appropriate time during a movement trial. The adaptive co-operative mode, on the other hand, is based on the idea of enabling task completion instead of completing the task for the subject. Both these therapy modes were designed to adapt to a stroke subject's motor ability, and thus encourage voluntary participation from the stroke subject. The two controllers were tested on three stroke subjects practicing robot-assisted reaching movements. The results from this testing demonstrate that an underactuated wearable exoskeleton, such as RUPERT, can be used for administering robot-assisted therapy, in a manner that encourages voluntary participation from the subject undergoing therapy

A flexible sensor technology for the distributed measurement of interaction pressure

We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted

Intelligent upper-limb exoskeleton using deep learning to predict human intention for sensory-feedback augmentation

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Although there are a few examples of exoskeletons, they need manual operations due to the absence of sensor feedback and no intention prediction of movements. Here, we introduce an intelligent upper-limb exoskeleton system that uses cloud-based deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle signals, which are simultaneously computed to determine the user's intended movement. The cloud-based deep-learning predicts four upper-limb joint motions with an average accuracy of 96.2% at a 200-250 millisecond response rate, suggesting that the exoskeleton operates just by human intention. In addition, an array of soft pneumatics assists the intended movements by providing 897 newton of force and 78.7 millimeter of displacement at maximum. Collectively, the intent-driven exoskeleton can augment human strength by 5.15 times on average compared to the unassisted exoskeleton. This report demonstrates an exoskeleton robot that augments the upper-limb joint movements by human intention based on a machine-learning cloud computing and sensory feedback.Comment: 15 pages, 6 figures, 1 table, Submitted for possible publicatio

Experience of Robotic Exoskeleton Use at Four Spinal Cord Injury Model Systems Centers

Background and Purpose: Refinement of robotic exoskeletons for overground walking is progressing rapidly. We describe clinicians\u27 experiences, evaluations, and training strategies using robotic exoskeletons in spinal cord injury rehabilitation and wellness settings and describe clinicians\u27 perceptions of exoskeleton benefits and risks and developments that would enhance utility. Methods: We convened focus groups at 4 spinal cord injury model system centers. A court reporter took verbatim notes and provided a transcript. Research staff used a thematic coding approach to summarize discussions. Results: Thirty clinicians participated in focus groups. They reported using exoskeletons primarily in outpatient and wellness settings; 1 center used exoskeletons during inpatient rehabilitation. A typical episode of outpatient exoskeleton therapy comprises 20 to 30 sessions and at least 2 staff members are involved in each session. Treatment focuses on standing, stepping, and gait training; therapists measure progress with standardized assessments. Beyond improved gait, participants attributed physiological, psychological, and social benefits to exoskeleton use. Potential risks included falls, skin irritation, and disappointed expectations. Participants identified enhancements that would be of value including greater durability and adjustability, lighter weight, 1-hand controls, ability to navigate stairs and uneven surfaces, and ability to balance without upper extremity support. Discussion and Conclusions: Each spinal cord injury model system center had shared and distinct practices in terms of how it integrates robotic exoskeletons into physical therapy services. There is currently little evidence to guide integration of exoskeletons into rehabilitation therapy services and a pressing need to generate evidence to guide practice and to inform patients\u27 expectations as more devices enter the market. Background and Purpose: Refinement of robotic exoskeletons for overground walking is progressing rapidly. We describe clinicians\u27 experiences, evaluations, and training strategies using robotic exoskeletons in spinal cord injury rehabilitation and wellness settings and describe clinicians\u27 perceptions of exoskeleton benefits and risks and developments that would enhance utility. Methods: We convened focus groups at 4 spinal cord injury model system centers. A court reporter took verbatim notes and provided a transcript. Research staff used a thematic coding approach to summarize discussions. Results: Thirty clinicians participated in focus groups. They reported using exoskeletons primarily in outpatient and wellness settings; 1 center used exoskeletons during inpatient rehabilitation. A typical episode of outpatient exoskeleton therapy comprises 20 to 30 sessions and at least 2 staff members are involved in each session. Treatment focuses on standing, stepping, and gait training; therapists measure progress with standardized assessments. Beyond improved gait, participants attributed physiological, psychological, and social benefits to exoskeleton use. Potential risks included falls, skin irritation, and disappointed expectations. Participants identified enhancements that would be of value including greater durability and adjustability, lighter weight, 1-hand controls, ability to navigate stairs and uneven surfaces, and ability to balance without upper extremity support. Discussion and Conclusions: Each spinal cord injury model system center had shared and distinct practices in terms of how it integrates robotic exoskeletons into physical therapy services. There is currently little evidence to guide integration of exoskeletons into rehabilitation therapy services and a pressing need to generate evidence to guide practice and to inform patients\u27 expectations as more devices enter the market