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| ID | Type | Description | Link |
|---|---|---|---|
| METC nummer 25-211 | Other Identifier | NedMec |
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The goal of this clinical trial is to demonstrate control of digital devices through a brain implant in people with spinal cord injury. The main question it aims to answer is efficient, independent, BCI-based control over digital devices in settings of daily living of an individual with SCI. In this project an advanced generation fully implantable BCI system will be used, the Brain InterChange (BIC) from CorTec.
Participants will be implanted with an electrode grid on the surface of the brain and an amplifier/transmitter on the skull, under the skin. Participation includes visits of researchers for recording and training at home, 1-3 times per week for one year. Extension of participation after one year is possible. If successful, the participant will be able to use the BCI at home independently, without the presence of a researcher.
Spinal Cord Injury (SCI) results in motor impairments in body parts innervated by the spinal cord below the site of the lesion. In addition to loss of leg movements, individuals with high cervical SCI experience significant impairments in arm and hand function (tetraplegia), impacting their access to digital devices, with obvious consequences for their ability to communicate, participate in society and the workforce, autonomously manage their life, and benefit from the entertainment options digital devices offer these days. Current assistive technologies (AT) for control over digital devices, such as voice control, eye-tracking, and head- or mouth-controlled devices, are often unintuitive, slow, limited in functionality, aesthetically unattractive, and they often interfere with regular movement or speech. An effective Brain-Computer Interface (BCI) would enable individuals with SCI to use movement-related neural signals to directly control digital devices, taking away the disadvantages of current AT. This would dramatically improve their quality of life.
The Brain InterChange from CorTec is an active implantable medical device for measurement of neuronal activity and electrical stimulation of the human nervous system, comprising an internal and an external unit. The internal unit consists of a small high-density ECoG grid with 32 contacts placed subdurally and a connected implantable amplifier/transmitter device that is placed subcutaneously. The external unit comprises a headpiece, for power transmission to the internal unit, a communication unit, that receives the data transmitted from the internal unit and controls the power transmission, and a USB cable, that connects the communication unit to the computer that has software to process and translate the brain data to a means of digital device control for SCI patients with custom in-house software developed during this study.
The BCI system also allows to provide users with somatosensory feedback about their motor attempts (in addition to the visual feedback), by delivering electrocortical stimulation (ECS) to the somatosensory regions of the brain. As such, the aim is to generate a more natural relation between intent (movement attempt of a body part) and effect (sensation in the same body part), which is expected to lead to fast training and accurate BCI performance.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| ECoG (electrocorticography) sensing | Experimental | Use implantable ECoG-based Brain Computer interface to control digital devices |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ECoG (electrocorticography) sensing | Device | Implant electrodes and amplifier/transmitter and use, through amplifier and decoding, for control of BCI |
|
| Measure | Description | Time Frame |
|---|---|---|
| Effectiveness of BCI Control: Accuracy | Accuracy: >80% sensitivity (true positive rate) for 1-command control; 80% classification accuracy (distinguishing between multiple classes) for multi-command control; and 80% classification accuracy and the correlation between the intended and actual response for multi-command continuous control | 1 year |
| Efficiency of BCI control: Speed | number of accurate selections made per minute | 1 year |
| Efficiency of BCI control: Subjective Workload - Visual Analogue Scale | Subjective Workload: Visual Analogue Scale Continuous scale: Little to no effort (0) - Much effort (5). Lower numbers are better. | 1 year |
| Efficiency of BCI control: Subjective Workload - National Aeronautics and Space Administration-Task Load Index | Subjective Workload: National Aeronautics and Space Administration-Task Load Index Scale: 21 point Likert-type scale. Lower numbers are better. | 1 year |
| User satisfaction Quebec User Evaluation of Satisfaction with assistive Technology (QUEST) | User Satisfaction: Quebec User Evaluation of Satisfaction with assistive Technology version 2.0. Likert-type scale: Extremely dissatisfied - Dissatisfied - Slightly satisfied - Satisfied - Extremely satisfied. Extremely Satisfied is the best result. | 1 year |
| user satisfaction Psychosocial impact of assistive devices scale (PIADS) | User Satisfaction: Psychosocial impact of assistive devices scale. Likert-type scale -3, -2, -1, 0, 1, 2, 3. 3 is best result. |
| Measure | Description | Time Frame |
|---|---|---|
| Assess device specifications for future, larger-scale, application of HD ECoG-BCIs | qualitative description on device specifications and experimental parameters, such as the specific decoder settings, for future, larger scale, application of HD ECoG-BCIs | 1 year |
| Validation of software for independent home-use of advanced BCIs |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Mariska J Vansteensel, PhD | Contact | +31887555121 | neuroprothese@umcutrecht.nl | |
| Erik J Aarnoutse, PhD | Contact | +31887555123 | e.j.aarnoutse@umcutrecht.nl |
| Name | Affiliation | Role |
|---|---|---|
| Nick F Ramsey, PhD | UMC Utrecht | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University Medical Center Utrecht | Recruiting | Utrecht | Utrecht | 3584CX | Netherlands |
selected datasets will be available through a public repository after publication of results
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after first published results, no end date
Publicly available
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| ID | Term |
|---|---|
| D013119 | Spinal Cord Injuries |
| D011782 | Quadriplegia |
| ID | Term |
|---|---|
| D013118 | Spinal Cord Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D020196 | Trauma, Nervous System |
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| ID | Term |
|---|---|
| D000069280 | Electrocorticography |
| ID | Term |
|---|---|
| D003943 | Diagnostic Techniques, Neurological |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D004568 | Electrodiagnosis |
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|
| 1 year |
| Stability of BCI performance: impedance | Longitudinally follow the electrode impedance (in Ω), to assess their stability throughout the day and across the weeks and months after implantation. | 1 year |
| Stability of BCI performance: signal dynamics | Longitudinally follow the raw signal dynamics (in µV) of neural signals, to assess their stability throughout the day and across the weeks and months after implantation. | 1 year |
| Stability of BCI performance: task-related modulation | Longitudinally follow the task-related modulation in power (in µV), to assess their stability throughout the day and across the weeks and months after implantation. | 1 year |
| Effects of somatosensory feedback on BCI Training and Performance: accuracy | Compare BCI control accuracy (in %), including variability and improvement therein before and after applying somatosensory feedback through electrocortical stimulation of the somatosensory cortex | 1 year |
| Effects of somatosensory feedback on BCI Training and Performance: neural signals | Compare neural signal changes (in µV) in the sensorimotor areas before and after applying somatosensory feedback through electrocortical stimulation of the somatosensory cortex | 1 year |
Validation: Questionnaire to evaluate user satisfaction and ease of use of the home use software. Likert-type scale: fully disagree - disagree - neither agree or disagree - agree - fully agree - not applicable. Fully agree is the best result. |
| 1 year |
| D014947 | Wounds and Injuries |
| D010243 | Paralysis |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |