ArticleFrontiers in human neuroscience2026
Graded multisensory neurofeedback via the iNems system for comprehensive upper limb recovery after stroke: a multiple baseline study.
Article in Frontiers in human neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Post-stroke upper-limb recovery remains challenging, especially in the presence of sensory impairments. Conventional brain-computer interfaces (BCIs) are constrained by binary feedback, single-modality stimulation, and exclusion of patients with sensory deficits. We developed the Imagery Neurofeedback-based Multi-sensory System (iNems), a neurofeedback system that provides graded multisensory (visual and electrical) feedback based on ERD magnitude. This study validated iNems' efficacy in motor function, self-reported numbness, and cognitive functions using a multiple-baseline design (MBD). Methods: Four participants with post-stroke upper-limb motor and sensory impairments underwent a multiple baseline design. The baseline phase (phase A) used random feedback; the intervention (phase B) used adaptive iNems. iNems quantified motor intention via sensorimotor EEG event-related desynchronization (ERD) and delivered graded visual and electrical feedback. Primary outcomes were the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and Box and Block Test (BBT). Secondary outcomes included body cognition, numbness, and neurophysiological (ERD/ERS) changes. Results: All participants demonstrated significant improvement during the intervention. FMA-UE increased by 6-16 points. The BBT showed large effects (integrated Tau-U = 0.75). Body cognition improved significantly in both sense of agency (Tau-U = 0.80) and ownership (Tau-U = 0.89). Numbness was reduced in affected cases (Tau-U = -0.85). Neurophysiological changes correlated with functional gains, with some patterns suggesting increased neural efficiency. Conclusion: This first MBD-validated demonstration shows that graded, multisensory graded neurofeedback based on ERD magnitude can improve motor, self-reported numbness, and cognitive domains after stroke. These findings support adaptive closed-loop therapy as a promising, multifaceted rehabilitation strategy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.