Brain-machine interfaces for effortless interactions with virtual/augmented environments

该项目的目标是创建一个原型脑机接口（BMI），允许专家在基于计算机的虚拟/增强现实（VR/AR）环境中轻松地与3D对象进行交互。BMI的关键推动者是软件算法，能够识别由非侵入性脑电图（EEG）捕获的脑电波的实时特征。识别的基础是我们独特的分析降阶模型的适应，它预测时间和空间上的动态非稳态流模式。原型BMI可作为原理证明，突出其设计、实现和使用，以减少认知工作量，促进轻松的用户交互。一旦得到改进，BMI将有利于阿尔伯塔省和加拿大的经济和社会，因为它促进了专家在各种应用中有效采用VR/AR环境，例如规划公共安全（例如，防洪减灾），提高工业竞争力（例如，反应堆设计和虚拟样机），以及创新可信赖的人机界面（例如，人机防御系统）。

The objective of the project is to create a prototype Brain-Machine Interface (BMI), allowing experts to interact effortlessly with 3D objects within computer-based virtual/augmented reality (VR/AR) environments. The key-enabler of the BMI is software algorithms, capable of identifying in real time characteristic features of brainwaves captured by a non-invasive electroencephalogram (EEG). Underlying the identification is our unique adaptation of analytical reduced-order models, which predict dynamic unsteady-flow patterns in time and space. The prototype BMI serves as a proof-of-principle to highlight its design, implementation, and use for reducing cognitive workload to promote effortless user interactions. Once improved, the BMI is beneficial for Albertan and Canadian economy and society by catalyzing effective adoption of VR/AR environments for experts' actions in various applications - such as planning public safety (e.g., flood mitigation), boosting industrial competitiveness (e.g., reactor design and virtual prototyping), and innovating trustable human-machine interfaces (e.g., human-robot defense systems).