Gait Adaptation Using a Cable-Driven Active Leg Exoskeleton (C-ALEX) With Post-Stroke Participants

Hidayah, Rand; Bishop, Lauri; Jin, Xin; Chamarthy, Siddharth; Stein, Joel; Agrawal, Sunil K.

doi:10.1109/tnsre.2020.3009317

Cited by 43 publications

(23 citation statements)

References 48 publications

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“…For partial assistance, it is associated with impedance control [13,145,182,[205][206][207]. These trajectories can be played back over time [89,205], or may be time-invariant (a tunnel or force field around the nominal path) [17,181,197,[208][209][210][211]. In [137], the reference profile is artificially generated and tuned to achieve a certain pattern of assistance.…”

Section: Action Sublayermentioning

confidence: 99%

“…A combination of both the force field and the flow field is suggested by Jabbari Asl et al [230]. Note that using a multi-dimensional force-field in foot-locus-space to assist the leg to follow a pre-defined trajectory (such as the strategy used in [211]) is time-invariant, and is not the same as playing back a reference trajectory, even if both are classified as impedance control.…”

Section: Action Sublayermentioning

confidence: 99%

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Review of control strategies for lower-limb exoskeletons to assist gait

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

164

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Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Methods In addition to covering the recent publications on the control of lower-limb exoskeletons for gait assistance, an effort has been made to review the controllers independently of the hardware and implementation aspects. The common 3-level structure (high, middle, and low levels) is first used to separate the continuous behavior (mid-level) from the implementation of position/torque control (low-level) and the detection of the terrain or user’s intention (high-level). Within these levels, different approaches (functional units) have been identified and combined to describe each considered controller. Results 291 references have been considered and sorted by the proposed classification. The methods identified in the high-level are manual user input, brain interfaces, or automatic mode detection based on the terrain or user’s movements. In the mid-level, the synchronization is most often based on manual triggers by the user, discrete events (followed by state machines or time-based progression), or continuous estimations using state variables. The desired action is determined based on position/torque profiles, model-based calculations, or other custom functions of the sensory signals. In the low-level, position or torque controllers are used to carry out the desired actions. In addition to a more detailed description of these methods, the variants of implementation within each one are also compared and discussed in the paper. Conclusions By listing and comparing the features of the reviewed controllers, this work can help in understanding the numerous techniques found in the literature. The main identified trends are the use of pre-defined trajectories for full-mobilization and event-triggered (or adaptive-frequency-oscillator-synchronized) torque profiles for partial assistance. More recently, advanced methods to adapt the position/torque profiles online and automatically detect terrains or locomotion modes have become more common, but these are largely still limited to laboratory settings. An analysis of the possible underlying reasons of the identified trends is also carried out and opportunities for further studies are discussed.

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Section: Action Sublayermentioning

confidence: 99%

Section: Action Sublayermentioning

confidence: 99%

Review of control strategies for lower-limb exoskeletons to assist gait

Baud

Manzoori

Ijspeert

et al. 2021

J NeuroEngineering Rehabil

164

View full text Add to dashboard Cite

show abstract

“…A few number of devices (25.6 %) did not implement any type of event detection algorithm for humanrobot synchronization, probably because they did not strictly need it [170][171][172][173][174][175][176]. Most of them were grounded exoskeletons that either enforced joint angle reference trajectories during gait -based on the unimpaired joint movement-using non-adaptive assistive control strategies [170, 171], or employed an adaptive assistive controller around the desired trajectory [172][173][174][175][176].…”

Section: High-level Control: Human-robot Synchronizationmentioning

confidence: 99%

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

Miguel-Fernández

Lobo-Prat²,

Prinsen

et al. 2022

Preprint

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BackgroundIn the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. Within this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) Providing an updated structured framework of current control strategies, (2) Analyzing the methodology of clinical validations used in the robotic interventions, and (3) Reporting the potential relation between the employed control strategies and clinical outcomes. MethodsFour databases were searched using database-specific search terms from 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy. Results(1) We found that adaptive assistive control (100 \% of exoskeletons) that followed rule-based algorithms (72 \%) based on ground reaction force thresholds (63 \%) in conjunction with trajectory-tracking control (97 \%) were the most implemented control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With moderate grade of evidence, associated to the high heterogeneity in the experimental protocol and low number of studies, we found that adaptive control strategies, which followed threshold-based or adaptive oscillator algorithms together with trajectory-tracking control, resulted in the highest improvements on clinical outcomes for people with stroke. ConclusionsDespite the efforts to develop novel more effective controllers for gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. The most promising controllers seem to be those that adapt to key biomechanical descriptors based on the patients' specific pathology.

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“…Jin et al utilized a force field controller for the C-ALEX exoskeleton to provide low-cost assistance [25]. To optimize C-ALEX's force for post-stroke participants, Hidayah et al evaluated the cable's force out of the plane movements relative to the desired tension magnitudes [26]. Hassan et al proposed a projection-based force distribution method for a 3-DOF parallel manipulator [27].…”

Section: Introductionmentioning

confidence: 99%

Design and Hierarchical Force-Position Control of Redundant Pneumatic Muscles-Cable-Driven Ankle Rehabilitation Robot

Liu

Zuo

Zhu

et al. 2022

IEEE Robot. Autom. Lett.

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Ankle dysfunction is common in the public following injuries, especially for stroke patients. Most of the current robotic ankle rehabilitation devices are driven by rigid actuators and have problems such as limited degrees of freedom, lack of safety and compliance, and poor flexibility. In this paper, we design a new type of compliant ankle rehabilitation robot redundantly driven by pneumatic muscles (PMs) and cables to provide full range of motion and torque ability for the human ankle with enhanced safety and adaptability, attributing to the PM's high power/mass ratio, good flexibility and lightweight advantages. The ankle joint can be compliantly driven by the robot with full three degrees of freedom to perform the dorsiflexion/plantarflexion, inversion/ eversion, and adduction/abduction training. In order to keep all PMs and cables in tension which is essential to ensure the robot's controllability and patient's safety, Karush-Kuhn-Tucker (KKT) theorem and analytic-iterative algorithm are utilized to realize a hierarchical force-position control (HFPC) scheme with optimal force distribution for the redundant compliant robot. Experiment results demonstrate that all PMs are kept in tension during the control while the position tracking accuracy of the robot is acceptable, which ensures controllability and stability throughout the compliant robot-assisted rehabilitation training.

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Gait Adaptation Using a Cable-Driven Active Leg Exoskeleton (C-ALEX) With Post-Stroke Participants

Cited by 43 publications

References 48 publications

Review of control strategies for lower-limb exoskeletons to assist gait

Review of control strategies for lower-limb exoskeletons to assist gait

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

Design and Hierarchical Force-Position Control of Redundant Pneumatic Muscles-Cable-Driven Ankle Rehabilitation Robot

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