Review of control strategies for lower-limb exoskeletons to assist gait.
Romain Baud, Ali Reza Manzoori, Auke Ijspeert and 1 others
PMID 34315499WHAT IT FOUND
Most successful full-mobilization exoskeletons rely on manual user input and pre-defined trajectories, while partial assistance devices perform best with event-triggered torque profiles.
This review maps the engineering control strategies but reports no clinical outcomes.
Key findings
01The most successful full-mobilization exoskeletons are controlled with manually selected modes, setting pre-defined trajectories that are manually or automatically triggered.
02For partial assistance, the best results have been obtained with event-triggered or adaptive-frequency oscillator-synchronized torque profiles, possibly tuned to each user.
03The review did not compare the performance of the controllers because target users, tasks, and experimental protocols differed too widely.
STILL TO COME
How it was doneWhat they found
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What it does not show
The review explicitly states that it does not compare the performance or effectiveness of the different control strategies. It is a technical engineering review focused on control algorithms, not on patient outcomes, functional independence, or clinical efficacy. The classification framework is described by the authors as not being a practical tool for designing new controllers or choosing between them for specific patients. The review excludes papers that do not provide enough detail on the control method, which typically includes clinical trial outcome papers.
Declared interests
The work was funded by Horizon 2020. The authors declared no other conflicts of interest.
The easy way to misread this
Do not interpret this review as evidence that any specific exoskeleton control strategy leads to better patient recovery or functional outcomes. The paper describes how the machines are programmed to move, not how well patients walk or improve with them.