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

Journal of NeuroEngineering and Rehabilitation

Review

Joan Lobo-Prat¹  Jesús de Miguel-Fernández²  Josep M. Font-Llagunes²  Laura Marchal-Crespo³  Erik Prinsen⁴ 

[1] ABLE Human Motion, Diagonal 647, 08028, Barcelona, Spain;Biomechanical Engineering Lab, Department of Mechanical Engineering and Research Centre for Biomedical Engineering, Universitat Politècnica de Catalunya, Diagonal 647, 08028, Barcelona, Spain;Institut de Recerca Sant Joan de Déu, Santa Rosa 39-57, 08950, Esplugues de Llobregat, Spain;Cognitive Robotics Department, Delft University of Technology, Mekelweg 2, 2628, Delft, Netherlands;Motor Learning and Neurorehabilitation Lab, ARTORG Center for Biomedical Engineering Research, University of Bern, Freiburgstrasse 3, 3010, Bern, Switzerland;Department of Rehabilitation Medicine, Erasmus MC University Medical Center, Doctor Molewaterplein 40, 3015, Rotterdam, GD, The Netherlands;Roessingh Research and Development, Roessinghsbleekweg 33b, 7522AH, Enschede, Netherlands;

关键词: Powered exoskeleton;    Gait rehabilitation;    Lower limb;    Brain injury;    Stroke;    Cerebral palsy;    Literature synthesis;   

DOI  :  10.1186/s12984-023-01144-5

 received in 2021-12-22, accepted in 2023-01-07,  发布年份 2023

来源: Springer

【 摘 要 】

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. In 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 control strategies and clinical outcomes.MethodsFour databases were searched using database-specific search terms from January 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 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. Only 14% of the exoskeletons implemented adaptive 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 high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented a combination of trajectory-tracking and compliant control showed the highest clinical effectiveness for acute stroke. However, they also required the longest training time. With high grade of evidence and low number of participants (N = 8), assistive control strategies that followed a threshold-based algorithm with EMG as gait detection metric and control signal provided the highest improvements with the lowest training intensities for subacute stroke. Finally, with high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented adaptive oscillator algorithms together with trajectory-tracking control resulted in the highest improvements with reduced training intensities for individuals with chronic stroke.ConclusionsDespite the efforts to develop novel and more effective controllers for exoskeleton-based 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. It is still an open question whether controllers that provide an on-line adaptation of the control parameters based on key biomechanical descriptors associated to the patients’ specific pathology outperform current control strategies.

【 授权许可】

CC BY   
© The Author(s) 2023

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