Low-burden, high-throughput brain-computer interfaces

低负担、高通量脑机接口

基本信息

  • 批准号:
    RGPIN-2019-06033
  • 负责人:
  • 金额:
    $ 4.66万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2022
  • 资助国家:
    加拿大
  • 起止时间:
    2022-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

CONTEXT A brain-computer interface (BCI) facilitates direct communication between the human brain and a computer and as such provides an attractive, potentially highly intuitive means of interacting with technology. Indeed, there has been a surge of interest in BCI applications in diverse industry sectors, including: home automation, military communications, gaming, geriatrics, assistive technology, and law enforcement, among others. However, current BCI technology requires arduous machine calibration and user training before a user's brain signals can be accurately recognized. Further, BCI-based communication remains slow compared to human face-to-face interaction. These challenges need to be overcome before the potential of BCIs can be broadly realized in society. OBJECTIVES The focus of my Discovery Grant is to tackle these challenges, specifically to: 1. Reduce the burden of machine calibration and user training, and 2. Increase the rate of BCI-based communication. PROPOSED RESEARCH To reduce the burden of calibration and training, we will investigate several technological approaches to accelerating machine and user learning. One method is to endow the BCI with a mathematical model developed for other users and to determine a way to efficiently adjust that model to a new user, while the user is also learning under the guidance of an expert. To increase the rate of BCI-based communication, we will deploy algorithms that understand the meaning of words spoken to a BCI user and subsequently present the BCI user with only messages that are relevant to the conversation at hand. We will develop a fast and intuitive way for the BCI user to select the desired message, simply by reading or imagining the words. ANTICIPATED OUTCOMES The proposed research will generate new ways for machines to learn to recognize changing brain patterns of a human user and new algorithms that help human users acquire the necessary skill to interact with technology via mental activity alone. This research will also yield a new and more efficient way to communicate with another human being via a BCI. Collectively, these outcomes will improve the practicality and usefulness of BCI technology. The proposed program will train 8 PhD students and up to 3 post-doctoral fellows. IMPORTANCE This research is of importance to Canadians living with severe disabilities. An easy-to-learn and fast BCI will open doors to educational attainment and eventual employment to those who are unable to communicate through speech or movements. This research will introduce to the BCI research field new theory and algorithms for concurrent machine and user learning, the notion of a BCI coach, evidence about the value of multisensory feedback and potentially new ways to detect user preference through brain signals. Finally, the program will assert a Canadian role in the burgeoning field of BCI by producing technologies that can be transferred to companies and BCI experts to lead the emerging sector.
脑机接口(BCI)促进了人脑和计算机之间的直接交流,因此提供了一种有吸引力的、潜在的高度直观的与技术交互的手段。事实上,人们对BCI在不同行业的应用兴趣激增,包括:家庭自动化、军事通信、游戏、老年医学、辅助技术和执法等。然而,目前的脑机接口技术需要艰苦的机器校准和用户培训,才能准确识别用户的大脑信号。此外,与人类面对面的交流相比,基于脑机接口的交流仍然缓慢。这些挑战需要克服,才能在社会上广泛实现脑机接口的潜力。我的探索基金的重点是解决这些挑战,特别是:1。减少了机器校准和用户培训的负担;提高基于bci的通信速率。为了减少校准和训练的负担,我们将研究几种加速机器和用户学习的技术方法。一种方法是赋予BCI为其他用户开发的数学模型,并确定一种方法来有效地调整该模型以适应新用户,同时用户也在专家的指导下学习。为了提高基于BCI的通信速率,我们将部署能够理解对BCI用户所说的单词的含义的算法,并随后仅向BCI用户提供与当前对话相关的消息。我们将开发一种快速和直观的方式,让BCI用户只需通过阅读或想象单词来选择所需的信息。预期结果拟议的研究将产生新的方法,让机器学习识别人类用户不断变化的大脑模式,并产生新的算法,帮助人类用户获得仅通过心理活动与技术互动的必要技能。这项研究还将产生一种新的、更有效的方式,通过脑机接口与另一个人交流。总的来说,这些结果将提高脑机接口技术的实用性和有用性。该计划将培养8名博士生和最多3名博士后。这项研究对患有严重残疾的加拿大人很重要。一个易于学习和快速的脑机接口将为那些无法通过语言或动作进行交流的人打开教育和最终就业的大门。这项研究将为BCI研究领域引入新的理论和算法,用于并发机器和用户学习,BCI教练的概念,关于多感官反馈价值的证据,以及通过大脑信号检测用户偏好的潜在新方法。最后,该项目将通过生产可转让给公司和BCI专家以领导新兴行业的技术,在新兴的BCI领域中确立加拿大的作用。

项目成果

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Chau, Tom其他文献

Towards a system-paced near-infrared spectroscopy brain-computer interface: differentiating prefrontal activity due to mental arithmetic and mental singing from the no-control state
  • DOI:
    10.1088/1741-2560/8/6/066004
  • 发表时间:
    2011-12-01
  • 期刊:
  • 影响因子:
    4
  • 作者:
    Power, Sarah D.;Kushki, Azadeh;Chau, Tom
  • 通讯作者:
    Chau, Tom
The effect of accelerometer location on the classification of single-site forearm mechanomyograms
  • DOI:
    10.1186/1475-925x-9-23
  • 发表时间:
    2010-06-10
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Alves, Natasha;Sejdic, Ervin;Chau, Tom
  • 通讯作者:
    Chau, Tom
Classifying Affective States Using Thermal Infrared Imaging of the Human Face
Stationarity distributions of mechanomyogram signals from isometric contractions of extrinsic hand muscles during functional grasping
An online three-class Transcranial Doppler ultrasound brain computer interface
  • DOI:
    10.1016/j.neures.2015.12.013
  • 发表时间:
    2016-06-01
  • 期刊:
  • 影响因子:
    2.9
  • 作者:
    Goyal, Anuja;Samadani, Ali-Akbar;Chau, Tom
  • 通讯作者:
    Chau, Tom

Chau, Tom的其他文献

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{{ truncateString('Chau, Tom', 18)}}的其他基金

Low-burden, high-throughput brain-computer interfaces
低负担、高通量脑机接口
  • 批准号:
    RGPIN-2019-06033
  • 财政年份:
    2021
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Low-burden, high-throughput brain-computer interfaces
低负担、高通量脑机接口
  • 批准号:
    RGPIN-2019-06033
  • 财政年份:
    2020
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Low-burden, high-throughput brain-computer interfaces
低负担、高通量脑机接口
  • 批准号:
    RGPIN-2019-06033
  • 财政年份:
    2019
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Intelligent systems for pediatric rehabilitation
儿科康复智能系统
  • 批准号:
    RGPIN-2014-06077
  • 财政年份:
    2018
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Intelligent systems for pediatric rehabilitation
儿科康复智能系统
  • 批准号:
    RGPIN-2014-06077
  • 财政年份:
    2017
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Intelligent systems for pediatric rehabilitation
儿科康复智能系统
  • 批准号:
    RGPIN-2014-06077
  • 财政年份:
    2016
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Intelligent systems for pediatric rehabilitation
儿科康复智能系统
  • 批准号:
    RGPIN-2014-06077
  • 财政年份:
    2015
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual
Unsupervised data-driven discovery for characterizing brain states
用于表征大脑状态的无监督数据驱动发现
  • 批准号:
    471066-2014
  • 财政年份:
    2014
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Engage Grants Program
NSERC CREATE Academic Rehabilitation Engineering (CARE) Training Program
NSERC CREATE 学术康复工程 (CARE) 培训计划
  • 批准号:
    370871-2009
  • 财政年份:
    2014
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Collaborative Research and Training Experience
Intelligent systems for pediatric rehabilitation
儿科康复智能系统
  • 批准号:
    RGPIN-2014-06077
  • 财政年份:
    2014
  • 资助金额:
    $ 4.66万
  • 项目类别:
    Discovery Grants Program - Individual

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