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2026-07-28 00:00 France Clinical Results & Follow-up Translated from EN

Hospices Civils de Lyon trial decodes motor imagery for stroke rehab

Summary Hospices Civils de Lyon has registered a clinical study in France to decode motor imagery from non-invasive brain recordings as a prerequisite for innovative motor rehabilitation therapies. Combining MRI, MEG, and EEG, the study will design a subject-specific neurophysiological model, noting that standard BCI approaches neglect transient features such as beta bursts. The approach will first be validated in healthy subjects, then assessed for feasibility in stroke patients.
Why it matters This study is among the first to incorporate transient features like beta bursts into non-invasive BCI decoding of motor imagery, challenging the traditional ERD/ERS paradigm based on averaged power. If successful, it could offer more precise BCI training for post-stroke motor rehabilitation. Currently at an early feasibility stage with few patients, results remain to be validated.

BCIwiki (bciwiki.com) — Hospices Civils de Lyon has registered a clinical study to decode motor imagery from non-invasive brain recordings as a prerequisite for innovative motor rehabilitation therapies. The study was first posted on ClinicalTrials.gov on July 28, 2026, under identifier NCT06469463, covering conditions such as stroke sequelae, motor imagery, and upper limb deficit, with interventions including MRI, MEG, and EEG.

The study notes that standard non-invasive brain-computer interface (BCI) approaches rely on event-related desynchronization (ERD) and event-related synchronization (ERS), which emerge only after averaging over multiple trials, thus neglecting transient features such as beta bursts in single trials. The researchers will use MRI and MEG to design a subject-specific neurophysiological model, employing an individualized head cast (hpMEG) to improve source localization accuracy, and will use this model to constrain online decoding of EEG data. The approach will be validated in healthy adults and compared against a classic EEG-based BCI, then assessed for feasibility in a few stroke patients with upper-limb motor deficits.

The team argues that beta bursts may carry more behaviorally relevant information than averaged beta band power, and that conventional signal processing methods, which assume sustained oscillations, are unsuitable for analyzing transient activity. This is an early feasibility study; specific results have not yet been reported.

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