iBCI Optimization for Veterans With Paralysis

Amyotrophic Lateral Sclerosis Clinical Trial

Official title:

Enhancement and Optimization of a Mobile iBCI for Veterans With Paralysis

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05470478
• Other study ID #: A3803-R
• Secondary ID: I01RX003803
• Status: Not yet recruiting
• Phase: N/A
• Start date: September 1, 2024
• Est. completion date: June 30, 2026

Study information

• Verified date: February 2024
• Source: VA Office of Research and Development
• Contact: Kate J Barnabe, MHA
• Phone: (401) 273-7100
• Email: Kate.Barnabe[@]va.gov
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 2
• Est. completion date: June 30, 2026
• Est. primary completion date: June 30, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

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).

Related Conditions & MeSH terms

• Amyotrophic Lateral Sclerosis
• Brain Stem Infarctions
• Locked-In Syndrome
• Motor Neuron Disease
• Muscular Dystrophies
• Muscular Dystrophy
• Paralysis
• Spinal Cord Injuries
• Spinal Cord Injury

Intervention

Device:
• Mobile 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.

Locations

Country	Name	City	State
United States	Providence VA Medical Center, Providence, RI	Providence	Rhode Island

Sponsors (1)

Lead Sponsor	Collaborator
VA Office of Research and Development

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Closed-loop performance in an iBCI cursor task	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.	through study completion, average of 1 month

External Links

•   This VA study does not create or modify a clinical trial. This Links to the associated clinical trial (IDE) which this particular VA study leverages.