ArticleJournal of neuroengineering and rehabilitation2026
Feasibility of AI-driven multichannel FES-assisted gait and cycling training in chronic neurological disorders: a case series.
Article in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Pattern-Matched Powered Gait Orthosis Training in Patients with Neurological Gait Impairment: A Multicenter Prospective Pilot Study of Hip and Knee-Ankle-Foot Orthoses.Journal of clinical medicine · 2026Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGait impairments following chronic neurological conditions, such as spinal cord injury (SCI), represent a major challenge for rehabilitation, with limited options to sustain functional recovery and patient engagement. Functional electrical stimulation (FES) has shown potential to enhance gait performance, but its integration into routine rehabilitation requires clinically feasible and acceptable solutions.
objectiveTo assess the feasibility, safety, and acceptability of integrating NeuroSkin®, a wearable AI-powered multichannel FES system, into walking rehabilitation programs for individuals with chronic neurological gait impairments, and to explore its potential to improve functional outcomes.
methodsThis retrospective case series included four individuals (three males, one female; aged 54-78 years) with chronic neurological gait impairments of diverse etiologies (acute disseminated encephalomyelitis, idiopathic transverse myelitis, incomplete spinal cord injury, and polyradiculoneuritis). Participants underwent 20 rehabilitation sessions over 6 weeks, which combined FES-assisted cycling and ambulation with the NeuroSkin device. The system integrates inertial measurement units and plantar pressure sensors to deliver phase-specific stimulation across multiple lower limb muscle groups. Feasibility was assessed through completion rates and adherence to the study protocol. Gait, balance, and spasticity outcomes were recorded before (PRE) and after the intervention (POST) with standardized assessments (10-Meter Walk Test, 2-Minute Walk Test, Berg Balance Scale, Stand Chair Test, Modified Ashworth Scale, SCATS, and Neuropathic Pain Diagnostic Questionnaire).
resultsAll participants completed the intervention, demonstrating good feasibility, tolerance, and adherence. Improvements were observed in walking speed and distance (10mWT and 2MWT), with concomitant improvement in lower limb strength and reductions in spasticity for three patients. These findings support the potential integration of AI-driven multichannel FES into long-term gait rehabilitation programs for individuals with chronic neurological conditions.
conclusionsThe integration of the NeuroSkin AI-driven FES system into rehabilitation programs for individuals with chronic neurological gait impairments was feasible, well accepted by patients, and safe. Furthermore, while improvements in gait performance were observed, these findings should be interpreted as exploratory and require confirmation in controlled studies.
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