Enhancement and Optimization of a Mobile iBCI for Veterans With Paralysis

Study Purpose:

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.

Study Status:

Not yet recruiting


Spinal Cord Injury , Amyotrophic Lateral Sclerosis , Brain Stem Infarctions , Locked-in Syndrome , Muscular Dystrophy

Study Type:


Type of Intervention:


Intervention Name:

Mobile neural decoding platform (mobile iBCI)





Study Chair(s)/Principal Investigator(s):

John D Simeral, PhD, Providence VA Medical Center, Providence, RI

Clinicaltrials.gov ID:


Neals Affiliated?


Coordinating Center Contact Information

Kate J Barnabe, MHA / email hidden; JavaScript is required / (401) 273-7100

Full Study Summary:

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.

Study Sponsor:

VA Office of Research and Development

Estimated Enrollment:


Estimated Study Start Date:

06 / 01 / 2023

Estimated Study Completion Date:

06 / 30 / 2026

Posting Last Modified Date:

05 / 15 / 2023

Date Study Added to neals.org:

07 / 22 / 2022

Minimum Age:

18 Years

Maximum Age:

80 Years

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:

- Exclusion criteria are extensive and are determined by the associated BrainGate IDE(clinicaltrials.gov # NCT00912041).

Providence VA Medical Center, Providence, RI

Kate J Barnabe, MHA / 401-273-7100 Ext. 16272 / email hidden; JavaScript is required

Principal Investigator : John D Simeral, PhD

Providence, Rhode Island 02908-4734
United States