Feasibility of AI-driven multichannel FES-assisted gait and cycling training in chronic neurological disorders: a case series.
Nikola Babić, Bernardo Fernandes De Sousa, Jonathan Levy and 5 others
PMID 41857636WHAT IT FOUND
People with chronic neurological gait impairments completed an AI-driven multichannel FES-assisted cycling and walking program.
All completed it, with a reversible swelling event; every participant had faster 10-meter walking and higher speed. The combined program's effect cannot be separated.
Key findings
01All participants completed the 6-week program, and one had bilateral reversible leg swelling at the end.
02Every participant had faster 10-meter walk times and higher 10-meter walk speeds from pre- to post-intervention.
03Berg Balance Scale scores increased for participants 1, 3, and 4, with no change for participant 2.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
Only four people were studied, and there was no control group, so the changes cannot be compared with another group. The participants had different diagnoses and baseline walking ability, so the result does not show what happens for any one condition. The training combined FES-assisted cycling and FES-assisted walking, so it cannot show which part produced the changes. Follow-up was only immediate after the program, so it does not show whether benefits lasted. No statistical testing was reported, and some outcomes changed differently across participants. Only participant 1 gave qualitative feedback. Stimulation intensity was set by comfort without a formal recruitment curve.
The easy way to misread this
Do not conclude that AI-driven FES alone caused the changes. Participants received FES-assisted cycling warm-up and FES-assisted walking together, and the authors state the contribution of cycling, walking, or FES cannot be separated.
Summarised by AI from the full paper, without a clinician reviewing it. Check it against the source before it changes what you do. Read it on PubMed →