Low-burden, high-throughput brain-computer interfaces

背景脑机接口(BCI)促进了人脑和计算机之间的直接交流，因此提供了一种吸引人的、潜在的高度直观的与技术互动的手段。事实上，在不同的行业领域，人们对BCI应用的兴趣激增，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BCI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-机接口的交流仍然很慢。需要克服这些挑战，才能在社会上广泛实现BCI的潜力。目标我的发现基金的重点是应对这些挑战，特别是：1.减少机器校准和用户培训的负担，2.提高基于脑-机接口的沟通的比率。为了减轻校准和培训的负担，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一个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的通信的速度，我们将部署理解BCI用户所说单词的含义的算法，并随后仅向BCI用户提供与手头对话相关的消息。我们将为BCI用户开发一种快速而直观的方式来选择所需的信息，只需阅读或想象单词。预期结果拟议中的研究将为机器提供新的方法来学习识别人类用户不断变化的大脑模式，并产生新的算法，帮助人类用户仅通过精神活动就能获得与技术互动所需的技能。这项研究还将产生一种新的、更有效的方式来通过脑机接口与另一个人交流。总的来说，这些成果将提高脑-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名博士后研究员。这项研究对生活在严重残疾中的加拿大人很重要。易学和快速的BCI将为那些无法通过语言或动作进行交流的人打开获得教育和最终就业的大门。这项研究将为BCI研究领域引入新的机器和用户学习的理论和算法，BCI教练的概念，多感觉反馈价值的证据，以及潜在的通过大脑信号检测用户偏好的新方法。最后，该计划将通过生产可转让给公司和BCI专家的技术来确立加拿大在新兴领域的作用，以领导新兴行业。

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.