Amyotrophic Lateral Sclerosis, Brain Stem Infarctions, Locked-in Syndrome, Muscular Dystrophy, Spinal Cord Injury
Conditions
Brief summary
VA research has been advancing a high-performance brain-computer interface (BCI) to improve independence for Veterans and others living with tetraplegia or the inability to speak resulting from amyotrophic lateral sclerosis, spinal cord injury or stoke. In this project, the investigators enhance deep learning neural network decoders and multi-state gesture decoding for increased accuracy and reliability and deploy them on a battery-powered mobile BCI device for independent use of computers and touch-enabled mobile devices at home. The accuracy and usability of the mobile iBCI will be evaluated with participants already enrolled separately in the investigational clinical trial of the BrainGate neural interface.
Detailed description
After VA IRB approval, this VA RR&D study will engage participants in the BrainGate clinical trial (IDE, sponsor-investigator LR Hochberg). This study does not create a new clinical trial or modify the existing clinical trial as already listed on clinicaltrials.gov This project builds on a custom, mobile neural signal processing device with exceptional processing and low power characteristics, which has been developed through previous VA RR&D funded research. This project takes advantage of the exceptional processing system, previously developed and validated, to create and quantify advanced neural decoding algorithms that show promise (in preclinical studies) for improving the accuracy and reliability of neural decoding - but that are likely too computationally demanding to be viable on existing real-time BCI systems. Decoding methods will include magnitude kinematic decoding with recursive neural networks and high-dimensional discrete gesture decoding. Computational methods to be evaluated include latent space methods and stable manifolds to improve day-to-day reliability of high performance and high-dimensional orthogonalization approaches to improve the independence of kinematic and gesture decoding.
Interventions
DEVICEMobile neural decoding platform (mobile iBCI)
An embedded neural signal processor device will be evaluated for its ability to provide accurate and reliable closed-loop control in a home-based brain-computer interface.
Sponsors
VA Office of Research and Development
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE
Intervention model description
Each participant enrolled in this early feasibility study is essentially an independent data point. The primary outcome of the IDE to which this VA study is attached is safety; feasibility is a secondary outcome. The outcome of this specific VA study, which engages participants in the BrainGate IDE, is usability of the mobile iBCI decoding system as measured through quantitative performance measures.
Eligibility
Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No
Inclusion criteria
* Inclusion criteria are extensive and are determined by the associated BrainGate IDE(clinicaltrials.gov # NCT00912041) * Informally, participants will be tetraplegic or anarthric with little or no functional use of the arms and legs
Exclusion criteria
*
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Closed-loop performance in an iBCI cursor task | through study completion, average of 1 month | Rate of successful closed-loop acquisition of on-screen targets using imagined gestures to move a computer cursor or to select icons on a computer screen. |
Countries
United States
Contacts
CONTACTKate J Barnabe, MHA
PRINCIPAL_INVESTIGATORJohn D Simeral, PhD
Providence VA Medical Center, Providence, RI
Outcome results
None listed