SBIR Phase I: A Hybrid Brain-Computer Interface for Virtual and Augmented Reality

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力解决了对非侵入性脑机接口（bci）和免提控制技术的需求，包括人工和虚拟现实（AR/VR）和智能设备。拟议的多用途脑机接口预计将立即应用于几个行业，包括制造业和医药。目前，现有的系统要么过于昂贵，要么无法进行实时控制。提议的BCI是专门为三维环境设计的，旨在利用来自人体的多个（“混合”）信号，通过使用价格合理的硬件来提高性能。它还为AR/VR控制而设计，这可以实现生产力应用程序，以及在现实场景中模拟BCI的使用。长期目标是让用户能够滚动菜单，选择对象，甚至使用他们的大脑活动来打字。该平台使用现有的AR/VR头显的外形因素来整合大脑感应电极，并将与流行的设备兼容，独立或与现有控制器并行。电极被设计成安全、无创、干燥（需要导电凝胶或生理盐水）。该项目将开展高风险、高回报的研究，将显著推进BCI系统的总体应用，重点是AR/VR技术。拟议的项目涉及一种新型混合脑机接口，通过定制的机器学习平台将动眼肌和脑电图（EEG）信号结合起来。脑机接口检测和解释神经信号，实现对各种技术的控制。然而，目前的脑机接口在其适用性方面仍然非常有限。它们要么需要昂贵的设备、侵入性手术，要么在使用负担得起的非侵入性硬件时性能太低。该BCI旨在提供三维场景的实时控制（例如，AR/VR/现实世界的智能设备），同时使用价格合理的硬件。SBIR第一阶段项目旨在结合三个不同的创新：高性能脑电图信号分析、高速眼动分类和定制多信号集成分类技术。具体来说，该项目寻求使用定制的机器学习和人工智能方法，根据生理学来结合眼动和脑电图信号，以实现3d AR/VR控制。最终目标是开发一种高性能BCI系统，该系统可以在硬件、软件和移动应用程序之间提供灵活的用户控制。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project addresses the need for non-invasive brain-computer interfaces (BCIs) and hands-free control of technologies, including artificial and virtual reality (AR/VR) and smart devices. The proposed multi-purposed BCI is expected to have immediate applications for several industries, including manufacturing and medicine. Currently, existing systems are either too expensive or limited for real-time control. The proposed BCI is specifically designed for 3 dimensional environments, and is intended to leverage multiple ('hybrid') signals from the human body to allow increased performance using affordable hardware. It is also designed for and expected to allow AR/VR control, which can enable productivity applications, as well as model BCI use in real-world scenarios. The long term goal is to enable users to scroll menus, select objects, and even type using their brain activity. The platform uses the existing form-factor of AR/VR headsets to incorporate brain-sensing electrodes, and will be compatible with popular devices, independently or in parallel with their existing controllers. The electrodes are designed to be safe, non-invasive, and dry (requiring conductive gel or saline). The high-risk, high-reward research to be conducted under this project will significantly advance the applications of BCI systems in general, with an emphasis on AR/VR technologies.The proposed project concerns a novel hybrid BCI by combining oculomotor and electroencephalography (EEG) signals via a custom machine learning platform. BCIs detect and interpret neural signals enabling control over a variety of technologies. However, current BCIs remain extremely limited in their applicability. They either require expensive equipment, invasive surgery, or have too low performance when using affordable noninvasive hardware. This BCI aims to provide real-time control in 3-dimensional scenarios, (e.g., AR/VR/real-world smart devices), while using affordable hardware. This SBIR Phase I project seeks to combine three distinct innovations: high-performance EEG signal analysis, high-speed eye movement classification, and custom multi-signal ensemble classification techniques. Specifically, the project seeks to use a custom machine learning and artificial intelligence approach informed by physiology to combine oculomotor and EEG signals to specifically enable3D AR/VR control. The ultimate goal is to develop a high performance BCI system that affords flexible user control across hardware, software, and mobile applications.