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.