Enhancement and Optimization of a Mobile iBCI for Veterans With Paralysis
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 2
- 试验地点
- 1
- 主要终点
- Closed-loop performance in an iBCI cursor task
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 80 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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
排除标准
- •Exclusion criteria are extensive and are determined by the associated BrainGate IDE(clinicaltrials.gov # NCT00912041).
研究组 & 干预措施
Evaluation of an enhanced 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.
干预措施: Mobile neural decoding platform (mobile iBCI) (Device)
结局指标
主要结局
Closed-loop performance in an iBCI cursor task
时间窗: 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.
次要结局
未报告次要终点