Deployment of a Mobile Broadband BCI

移动宽带 BCI 的部署

基本信息

  • 批准号:
    10661494
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-07-01 至 2023-06-30
  • 项目状态:
    已结题

项目摘要

1 Intracortical neural interfaces, which record and analyze streams of neural signals recorded 2 from arrays of electrodes implanted in the brain, can enable fast, accurate, intuitive control of 3 enabling assistive technologies for individuals with paralysis arising from spinal cord injury as 4 well as other neurological conditions including stroke and ALS. Individuals with tetraplegia in the 5 pilot clinical trial of the BrainGate (IDE*) intracortical neural interface system use imagined 6 movements of their own paralyzed hand and arm to command point-and-click with a computer 7 cursor (on-screen typing, communication apps such as chat, web browsing) and to control 8 assistive devices including the DEKA prosthetic arm/hand, assistive robots and even reach and 9 grasp with one’s own paralyzed limb reanimated through patterned stimulation of the paralyzed 10 muscles. These BrainGate activities take place in study participants’ homes, but the need for a 11 recording cable tethered between the participant and a large rack of signal processing 12 computers dictates that the iBCI can only be used under direct technical supervision during 13 dedicated research periods. However, with the recent availability of a high-bandwidth, miniature 14 wireless neural signal transmitter (to eliminate the tethering cable) and a state-of-the-art 15 compact signal processing device with sufficient computational resources to execute the 16 BrainGate algorithms, the components are available to enable trial participants and caregivers 17 to use and administer a wireless, mobile intracortical brain-computer interface (iBCI) at home to 18 enable on-demand digital access throughout day and night and throughout the home. 19 This study aims to evaluate the feasibility and utility of an iBCI deployed in a mobile package 20 for independent use at home without technical supervision. In addition to evaluating the new 21 mobile platform, this will demonstrate the first-ever in-home use of an intracortical BCI without 22 direct technical oversight. End users and caregivers will be trained to configure and operate the 23 iBCI. With the iBCI mounted to their wheelchair and a chair-mounted consumer tablet, end 24 users with tetraplegia will be able to use their own imagined arm and hand movements to 25 control familiar tablet “apps” on demand anywhere in the home. Moving the mobile iBCI to the 26 bedside will enable tablet use from bed or neural signal monitoring through the night. 27 Before deployment, the current prototype mobile iBCI - developed in recent VA funded 28 research - will be provisioned with the most recent state-of-the-art signal processing and neural 29 decoding algorithms developed in the BrainGate pilot clinical trial. This will involve translating 30 those real-time software algorithms into hardware description language to program the ultra- 31 low-power System-on-Chip device. Recent algorithms to be incorporated will enable rapid, 32 automatic calibration of the BCI without expert intervention; maintain calibration over longer 33 periods of time to reduce the need for explicit recalibration steps; and improve the speed and 34 accuracy of cursor trajectories derived from the user’s neural signals. Each of three users will 35 evaluate the system over a continuous 5 to 10 day period, and repeat the home assessment in 36 at least 3 consecutive months. Throughout, the technical operation of the BCI system and the 37 BrainGate algorithms will be monitored and evaluated quantitatively. In addition, user and 38 caregivers will complete questionnaires measuring their evolving satisfaction with the system 39 and its utility. Analyses of these cumulative data will inform future device improvements. 40 *CAUTION:Investigational Device.Limited by Federal (United States) Law to Investigational Use
1 皮质内神经接口,记录和分析记录的神经信号流 2.由植入大脑的电极阵列,可以实现快速、准确、直观的控制 3 为因脊髓损伤而瘫痪的人提供辅助技术 4 以及其他神经系统疾病,包括中风和 ALS。四肢瘫痪的人 BrainGate (IDE*) 皮质内神经接口系统使用想象的 5 个试点临床试验 他们自己瘫痪的手和手臂的 6 种动作,用于通过计算机进行点击操作 7 光标(屏幕打字、聊天、网页浏览等通讯应用)并进行控制 8种辅助设备,包括DEKA假臂/手、辅助机器人,甚至伸手和 9 通过对瘫痪者进行图案化刺激,用自己的瘫痪肢体进行抓握 10块肌肉。这些 BrainGate 活动在研究参与者的家中进行,但需要 11 条记录电缆连接在参与者和大型信号处理机架之间 12 台计算机规定 iBCI 只能在直接技术监督下使用 13个专门研究期。然而,随着最近高带宽、微型 14个无线神经信号发射器(消除束缚电缆)和最先进的 15 紧凑型信号处理设备,具有足够的计算资源来执行 16 个 BrainGate 算法,这些组件可供试验参与者和护理人员使用 17 在家中使用和管理无线移动皮质内脑机接口 (iBCI) 18 可以全天候、全家实现按需数字访问。 19 本研究旨在评估在移动设备中部署 iBCI 的可行性和实用性 20个在家独立使用,无需技术监督。除了评估新 21 移动平台,这将展示首次在家庭中使用皮质内 BCI,而无需 22 直接技术监督。最终用户和护理人员将接受配置和操作的培训 23 国际脑机接口。将 iBCI 安装到轮椅上和安装在椅子上的消费者平板电脑后,结束 24 位四肢瘫痪的用户将能够使用自己想象的手臂和手部动作来 25 在家中任何地方按需控制熟悉的平板电脑“应用程序”。将移动 iBCI 移至 26 床边将允许在床上使用平板电脑或整晚进行神经信号监测。 27 在部署之前,当前的移动 iBCI 原型 - 最近由 VA 资助开发 28项研究——将配备最新最先进的信号处理和神经网络 BrainGate 试点临床试验中开发了 29 种解码算法。这将涉及翻译 30 那些实时软件算法转化为硬件描述语言来编程超 31 低功耗片上系统器件。最近纳入的算法将能够实现快速、 32. BCI自动校准,无需专家干预;保持校准时间更长 33 个时间段,减少显式重新校准步骤的需要;并提高速度和 34 光标轨迹的准确性源自用户的神经信号。三个用户中的每一个将 35 在连续 5 至 10 天的时间内评估系统,并在 36 至少连续 3 个月。自始至终,BCI系统的技术操作和 37 个 BrainGate 算法将受到定量监控和评估。此外,用户和 38 名护理人员将完成调查问卷,衡量他们对系统不断变化的满意度 39 及其效用。对这些累积数据的分析将为未来的设备改进提供信息。 40 *注意:研究设备。受联邦(美国)法律限制,只能用于研究用途

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

John David Simeral其他文献

John David Simeral的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('John David Simeral', 18)}}的其他基金

Enhancement and optimization of a mobile iBCI for Veterans with paralysis
为瘫痪退伍军人增强和优化移动 iBCI
  • 批准号:
    10538008
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
Enhancement and optimization of a mobile iBCI for Veterans with paralysis
为瘫痪退伍军人增强和优化移动 iBCI
  • 批准号:
    10674504
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
Deployment of a Mobile Broadband BCI
移动宽带 BCI 的部署
  • 批准号:
    10339314
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Mobile Signal Processing System for Broadband Neural Decoding
用于宽带神经解码的移动信号处理系统
  • 批准号:
    9000722
  • 财政年份:
    2014
  • 资助金额:
    --
  • 项目类别:
Mobile Signal Processing System for Broadband Neural Decoding
用于宽带神经解码的移动信号处理系统
  • 批准号:
    8597512
  • 财政年份:
    2014
  • 资助金额:
    --
  • 项目类别:
Mobile Signal Processing System for Broadband Neural Decoding
用于宽带神经解码的移动信号处理系统
  • 批准号:
    9186959
  • 财政年份:
    2014
  • 资助金额:
    --
  • 项目类别:

相似海外基金

Medcircuit, the algorithmic software reducing waiting times in emergency department and general practice waiting rooms.
MedCircuit,一种算法软件,可减少急诊科和全科候诊室的等待时间。
  • 批准号:
    133416
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
    Feasibility Studies
SHF: Small: Programming Abstractions for Algorithmic Software Synthesis
SHF:小型:算法软件综合的编程抽象
  • 批准号:
    0916351
  • 财政年份:
    2009
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了