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      A Pediatric Knee Exoskeleton With Real-Time Adaptive Control for Overground Walking in Ambulatory Individuals With Cerebral Palsy

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          Abstract

          Gait training via a wearable device in children with cerebral palsy (CP) offers the potential to increase therapy dosage and intensity compared to current approaches. Here, we report the design and characterization of a pediatric knee exoskeleton (P.REX) with a microcontroller based multi-layered closed loop control system to provide individualized control capability. Exoskeleton performance was evaluated through benchtop and human subject testing. Step response tests show the averaged 90% rise was 26 ± 0.2 ms for 5 Nm, 22 ± 0.2 ms for 10 Nm, 32 ± 0.4 ms for 15 Nm. Torque bandwidth of P.REX was 12 Hz and output impedance was less than 1.8 Nm with control on (Zero mode). Three different control strategies can be deployed to apply assistance to knee extension: state-based assistance, impedance-based trajectory tracking, and real-time adaptive control. One participant with typical development (TD) and one participant with crouch gait from CP were recruited to evaluate P.REX in overground walking tests. Data from the participant with TD were used to validate control system performance. Kinematic and kinetic data were collected by motion capture and compared to exoskeleton on-board sensors to evaluate control system performance with results demonstrating that the control system functioned as intended. The data from the participant with CP are part of a larger ongoing study. Results for this participant compare walking with P.REX in two control modes: a state-based approach that provided constant knee extension assistance during early stance, mid-stance and late swing (Est+Mst+Lsw mode) and an Adaptive mode providing knee extension assistance proportional to estimated knee moment during stance. Both were well tolerated and significantly improved knee extension compared to walking without extension assistance (Zero mode). There was less reduction in gait speed during use of the adaptive controller, suggesting that it may be more intuitive than state-based constant assistance for this individual. Future work will investigate the effects of exoskeleton assistance during overground gait training in children with neurological disorders and will aim to identify the optimal individualized control strategy for exoskeleton prescription.

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          Most cited references38

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          Review of control strategies for robotic movement training after neurologic injury

          There is increasing interest in using robotic devices to assist in movement training following neurologic injuries such as stroke and spinal cord injury. This paper reviews control strategies for robotic therapy devices. Several categories of strategies have been proposed, including, assistive, challenge-based, haptic simulation, and coaching. The greatest amount of work has been done on developing assistive strategies, and thus the majority of this review summarizes techniques for implementing assistive strategies, including impedance-, counterbalance-, and EMG- based controllers, as well as adaptive controllers that modify control parameters based on ongoing participant performance. Clinical evidence regarding the relative effectiveness of different types of robotic therapy controllers is limited, but there is initial evidence that some control strategies are more effective than others. It is also now apparent there may be mechanisms by which some robotic control approaches might actually decrease the recovery possible with comparable, non-robotic forms of training. In future research, there is a need for head-to-head comparison of control algorithms in randomized, controlled clinical trials, and for improved models of human motor recovery to provide a more rational framework for designing robotic therapy control strategies.
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            Design and Evaluation of the LOPES Exoskeleton Robot for Interactive Gait Rehabilitation

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              Motor learning elicited by voluntary drive.

              Motor training consisting of voluntary movements leads to performance improvements and results in characteristic reorganizational changes in the motor cortex. It has been proposed that repetition of passively elicited movements could also lead to improvements in motor performance. In this study, we compared behavioural gains, changes in functional MRI (fMRI) activation in the contralateral primary motor cortex (cM1) and in motor cortex excitability measured with transcranial magnetic stimulation (TMS) after a 30 min training period of either voluntarily (active) or passively (passive) induced wrist movements, when alertness and kinematic aspects of training were controlled. During active training, subjects were instructed to perform voluntary wrist flexion-extension movements of a specified duration (target window 174-186 ms) in an articulated splint. Passive training consisted of wrist flexion- extension movements elicited by a torque motor, of the same amplitude and duration range as in the active task. fMRI activation and TMS parameters of motor cortex excitability were measured before and after each training type. Motor performance, measured as the number of movements that hit the target window duration, was significantly better after active than after passive training. Both active and passive movements performed during fMRI measurements activated cM1. Active training led to more prominent increases in (i) fMRI activation of cM1; (ii) recruitment curves (TMS); and (iii) intracortical facilitation (TMS) than passive training. Therefore, a short period of active motor training is more effective than passive motor training in eliciting performance improvements and cortical reorganization. This result is consistent with the concept of a pivotal role for voluntary drive in motor learning and neurorehabilitation.
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                Author and article information

                Contributors
                Journal
                Front Robot AI
                Front Robot AI
                Front. Robot. AI
                Frontiers in Robotics and AI
                Frontiers Media S.A.
                2296-9144
                18 June 2021
                2021
                : 8
                : 702137
                Affiliations
                [ 1 ]Biomedical Engineering Program, Department of Mechanical Engineering, University of the District of Columbia, Washington, DC, United States
                [ 2 ]Rehabilitation Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD, United States
                Author notes

                Edited by: Noman Naseer, Air University, Pakistan

                Reviewed by: Jessica Rose, Stanford University, United States

                Rayyan Azam Khan, University of Saskatchewan, Canada

                Umar Shahbaz Khan, National University of Sciences and Technology, Pakistan

                *Correspondence: Thomas C. Bulea, thomas.bulea@ 123456nih.gov

                This article was submitted to Biomedical Robotics, a section of the journal Frontiers in Robotics and AI

                Article
                702137
                10.3389/frobt.2021.702137
                8249803
                34222356
                9efb3bc1-1813-4882-92ad-84d389928cc4
                Copyright © 2021 Chen, Hochstein, Kim, Tucker, Hammel, Damiano and Bulea.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 April 2021
                : 27 May 2021
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Categories
                Robotics and AI
                Original Research

                pediatric knee exoskeleton,real-time adaptive control,crouch gait,finite state machine,torque assistance,cerebral palsy

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