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The BCI project falls within the very broad field of brain machine interfaces. Its multiple applications include the compensation of motor deficits. The subject of the present protocol is the first test of the system in man on the compensation of motor deficits by an epidural brain implant enabling an electrocorticogram (EcoG) to be recorded.
Injuries to the cervical spine and to its contents, the spinal cord, cause serious neurological deficits, with loss of motor function and sensitivity of the four limbs, resulting in quadriplegia. The level of the lesion separating the area without deficits, above the lesion, from the sub-lesional area depends on the extent of the spine injury (dislocation, fracture or trauma without final displacement), may cause spinal cord injuries of varying severity, which can range from the benign to a complete section that results in complete and irreversible sensorimotor deficits. Lesions from C1 to C4 are often immediately fatal or cause diaphragmatic paralysis (innervated by the phrenic nerve whose roots originate at C4). C4-C5 paraplegia and below are therefore compatible with life as they spare respiratory autonomy, although they lead to severe permanent disabilities, creating a state of severe dependence in subjects who are often young.
The problems created by these patients are those of an extremely heavy individual, family, and societal burden in addition to the individual drama. While paraplegics, by maintaining their motor skills and sensitivity of both upper limbs and back muscles can often reintegrate and find remarkable mobility with wheelchairs, this is not the case of quadriplegics who must be provided with substitutes in order to achieve an acceptable quality of life. This project offers a highly innovative approach by means of a motorized exoskeleton that enables standing, walking and the use of the upper extremities. The validation of the first step of this concept will pave the way for developing increasingly sophisticated exoskeletal neuroprostheses, aimed at giving these patients compatible and ever greater autonomy.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| BCI | Experimental | Brain-computer interface (BCI) platform including two implanted remotely powered ElectroCorticoGraph (ECoG) recording devices and an exoskeleton |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Brain-computer interface (BCI) platform including two implanted remotely powered ElectroCorticoGraph (ECoG) recording devices and an exoskeleton | Device |
|
| Measure | Description | Time Frame |
|---|---|---|
| Number of Participants with Adverse Events | Complications associated with the chronic implantation of an extradural ECoG measuring implant. | 4 years after surgery |
| Measure | Description | Time Frame |
|---|---|---|
| Patient's level of performance in piloting the degrees of freedom of the exoskeleton | To test the feasibility of compensation of motor deficits due to spinal trauma by a motorized man-machine interface neuroprosthesis controlled by cortical commands from biomarkers extracted from the ECoG. | 4 years after surgery |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Stéphan CHABARDES, MD, PhD | Contact | + 33 4 76 76 75 59 | SChabardes@chu-grenoble.fr | |
| Caroline SANDRE-BALLESTER, PhD | Contact | + 33 4 38 78 28 51 | csandreballester@chu-grenoble.fr |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| CLINATEC | Recruiting | Grenoble | 38000 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31587955 | Background | Benabid AL, Costecalde T, Eliseyev A, Charvet G, Verney A, Karakas S, Foerster M, Lambert A, Moriniere B, Abroug N, Schaeffer MC, Moly A, Sauter-Starace F, Ratel D, Moro C, Torres-Martinez N, Langar L, Oddoux M, Polosan M, Pezzani S, Auboiroux V, Aksenova T, Mestais C, Chabardes S. An exoskeleton controlled by an epidural wireless brain-machine interface in a tetraplegic patient: a proof-of-concept demonstration. Lancet Neurol. 2019 Dec;18(12):1112-1122. doi: 10.1016/S1474-4422(19)30321-7. Epub 2019 Oct 3. | |
| 34425566 |
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| Patient's quality of life evaluation |
Perception by the subject of changes in quality of life. Decrease in dependence on care environment. |
| 4 years after surgery |
| Background |
| Larzabal C, Bonnet S, Costecalde T, Auboiroux V, Charvet G, Chabardes S, Aksenova T, Sauter-Starace F. Long-term stability of the chronic epidural wireless recorder WIMAGINE in tetraplegic patients. J Neural Eng. 2021 Sep 9;18(5). doi: 10.1088/1741-2552/ac2003. |
| Background | Detection of Error Correlates in the Motor Cortex in a Long Term Clinical Trial of ECoG based Brain Computer Interface DOI: 10.5220/0010227800260034 |
| 39854845 | Derived | Bellicha A, Struber L, Pasteau F, Juillard V, Devigne L, Karakas S, Chabardes S, Babel M, Charvet G. Depth-sensor-based shared control assistance for mobility and object manipulation: toward long-term home-use of BCI-controlled assistive robotic devices. J Neural Eng. 2025 Feb 14;22(1). doi: 10.1088/1741-2552/adae36. |
| 37007675 | Derived | Sliwowski M, Martin M, Souloumiac A, Blanchart P, Aksenova T. Impact of dataset size and long-term ECoG-based BCI usage on deep learning decoders performance. Front Hum Neurosci. 2023 Mar 16;17:1111645. doi: 10.3389/fnhum.2023.1111645. eCollection 2023. |
| 35287119 | Derived | Sliwowski M, Martin M, Souloumiac A, Blanchart P, Aksenova T. Decoding ECoG signal into 3D hand translation using deep learning. J Neural Eng. 2022 Mar 31;19(2). doi: 10.1088/1741-2552/ac5d69. |
| 35234665 | Derived | Moly A, Costecalde T, Martel F, Martin M, Larzabal C, Karakas S, Verney A, Charvet G, Chabardes S, Benabid AL, Aksenova T. An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic. J Neural Eng. 2022 Mar 30;19(2). doi: 10.1088/1741-2552/ac59a0. |
| 33770779 | Derived | Larzabal C, Auboiroux V, Karakas S, Charvet G, Benabid AL, Chabardes S, Costecalde T, Bonnet S. The Riemannian spatial pattern method: mapping and clustering movement imagery using Riemannian geometry. J Neural Eng. 2021 Apr 8;18(5). doi: 10.1088/1741-2552/abf291. |
| ID | Term |
|---|---|
| D062207 | Brain-Computer Interfaces |
| D000069280 | Electrocorticography |
| ID | Term |
|---|---|
| D055615 | Electrical Equipment and Supplies |
| D004864 | Equipment and Supplies |
| D003943 | Diagnostic Techniques, Neurological |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D004568 | Electrodiagnosis |
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