iBCI Optimization for Veterans With Paralysis

Not Applicable

Not yet recruiting

• Conditions: Amyotrophic Lateral Sclerosis; Spinal Cord Injury; Locked-in Syndrome; Brain Stem Infarctions; Muscular Dystrophy
• Interventions: Device: Mobile neural decoding platform (mobile iBCI)

• Registration Number: NCT05470478
• Lead Sponsor: VA Office of Research and Development

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.

Study Timeline

• Study First Submitted: 2022-07-18
• Study First Submitted QC: 2022-07-20
• Study First Posted: 2022-07-22
• Status Verified: 2025-01
• Last Update Submitted: 2025-01-14
• Last Update Posted: 2025-01-15
• Study Start: 2025-09-01
• Primary Completion: 2026-06-30
• Study Completion: 2026-06-30

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 2

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).

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Evaluation of an enhanced iBCI	Mobile neural decoding platform (mobile iBCI)	Performance of new decoding algorithms and methods will be developed and embedded in a small, mobile neural processor. The utility of these will be assessed separately with participants in the BrainGate pilot clinical trial, IDE.

Primary Outcome Measures

Name	Time	Method
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.

Trial Locations

Locations (1)

Providence VA Medical Center, Providence, RI; 🇺🇸 Providence, Rhode Island, United States