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)，使专家能够在基于计算机的虚拟/增强现实(VR/AR)环境中毫不费力地与3D对象交互。BMI的关键使能是软件算法，能够实时识别由非侵入性脑电(EEG)捕获的脑波的特征特征。识别的基础是我们对分析降阶模型的独特适应，这些模型预测了时间和空间上的动态非定常流动模式。原型BMI用作原则证明，以突出其设计、实现和用于减少认知工作量，以促进轻松的用户交互。BMI一旦得到改善，将促进VR/AR环境的有效采用，供专家在各种应用中采取行动，如规划公共安全(如洪水缓解)、提升工业竞争力(如反应堆设计和虚拟原型制作)以及创新可信赖的人机界面(如人机交互系统)，从而对艾伯坦和加拿大的经济和社会有利。

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).