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| Name | Class |
|---|---|
| Université Montpellier | OTHER |
| National University of Ireland, Maynooth | OTHER |
| Centre Hospitalier Universitaire de NÄ«mes | OTHER |
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The goal is to evaluate the potential of a EEG based BCI (Brain-Computer-Interface) connected to a non-invasive pneumatic glove for rehabilitation of hand-movements post-stroke.
Brain computer interfaces (BCI) encompasses the usage of the brain signals to compensate for lost physical function. The current protocol evaluates the therapeutic potential of a EEG based driven BCI that is connected to a non-invasive pneumatic glove for rehabilitation of hand flexion/extension post-stroke. The system non-invasive, portable and low-cost. The utility and usability of the system will be investigated at two levels. First by means of questionnaires for patients and therapist and second by means of in depth analysis of the EEG signals during intended, imagined and passive driven hand movements in relation to no movement at all and the capacity of the BCI to distinguish between these conditions.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Chronic post-stroke | Experimental | Patients >6 months post-stroke with little to no hand movement. use of EEG based BCI in the neurorehabilitation process |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| EEG based Brain Computer Interface | Device | Using EEG signals to classify brain activity being 'rest' or 'active' to control the attached pneumatic glove and close the sensory-motor loop between intentional/mental movement and physical (though passive) movement. |
| Measure | Description | Time Frame |
|---|---|---|
| Performance of the BCI-system (evaluation of performance through patient questionaires & the performance of the BCI classifier during intended and imagined hand movements) | Evaluation of the BCI-platform performance through patient questionnaires & the performance of the BCI classifier during intended and imagined hand movements. | During the whole study. Assesment is made for each patient after his participation ( 2 hours). |
| Measure | Description | Time Frame |
|---|---|---|
| EEG sensory-motor rhythm signals (Detailed analysis of the EEG signals in relation to the severity of the paresis and movement condition) | Detailed analysis of the EEG signals in relation to the severity of the paresis and movement condition | During the whole studyAssesment is made for each patient after his participation ( 2 hours). |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Liesjet Van Dokkum, PhD | CHRU Montpellier, Lapeyronie // Euromov-M2H, Montpellier University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| CHRU Lapeyronie | Montpellier | Herault | 34295 | France |
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| ID | Term |
|---|---|
| D020521 | Stroke |
| ID | Term |
|---|---|
| D002561 | Cerebrovascular Disorders |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |