CAREER: Signal Models, Channel Capacity, and Information Rate for Noninvasive Brain Interfaces

PI的最终研究目标是赋予严重言语和身体残疾的人权力，使他们能够最大限度地独立和富有成效地生活。为此，他将在这个项目中开发和推进新兴的脑机接口(BCI)技术，在BCI设计的背景下，严格开发脑电(EEG)测量的大脑视觉诱发电位(VEP)的宏观动态模型。这些模型将能够对BCI的通信渠道进行解释，并将使分析和设计突破源于信息论和数字通信概念的应用。皮层动力学和背景过程将使用概率动力学框架在适合于脑-机接口分析和设计的时空尺度上进行建模。然后将确定基于模型的带宽和校准精度的性能限制，以便开发更好的信息编码技术，以优化通信带宽(速度)的利用，并更好地进行主题培训和模型校准程序，以获得最大的投资回报。将实施原型实时应用程序，这些应用程序利用开发的通信和控制方面的理论进步，在最佳或接近最佳的性能水平下运行，以实现目标用户群体的访问并支持其独立性。项目成果将颠覆黑箱BCI设计的趋势，为BCI应用中遇到的刺激-脑电信号系统建立动态系统模型，并将其视为随机通信通道，以便相应地表征信号并使用信息论方法进行分析和设计。这一新颖的理论框架将使BCI性能极限能够基于模型进行量化表征，并将允许设计最优或接近最优的编码/解码策略以及改进的校准程序，这些策略将立即对增加带宽和意图检测精度产生影响，并缩短BCI系统中的校准持续时间-实验室原型和具有现实价值的BCI产品之间的主要障碍。广泛的影响：如果成功，该项目将把BCI技术推进到一个新的水平，从而使人机交互发生革命性变化，并通过实现对计算机和设备的无缝控制来增强肢体残疾人士的能力。该项目将通过与东北大学地下传感和成像系统中心(CenSSIS)以及各系和机构的同事合作，为本科工程和非工程专业的学生提供机会，通过让他们沉浸在具有社会影响的跨学科尖端研究和设计项目中来增强学习和协作技能。PI将通过他所在机构的STEM教育中心让高中生和教师参与这项研究。他将向更广泛的公众通报BCI领域正在进行的技术进步，并通过与波士顿科学博物馆的Cahners ComputerPlace合作提高残疾意识。

The PI's ultimate research goal is to empower people with severe speech and physical impairments so they can live their lives to the fullest extent independently and productively. To this end, he will in this project exploit and advance emerging brain computer interface (BCI) technology by rigorously developing macro-level dynamic models for the visual evoked potentials (VEP) in the brain measured by electroencephalography (EEG) in the context of BCI design. The models will enable a communication channel interpretation of the BCI and will allow analysis and design breakthroughs stemming from the application of information theory and digital communication concepts. Cortical dynamics and background processes will be modeled using a probabilistic dynamic framework at a spatiotemporal scale appropriate for BCI analysis and design. Model-based performance limits on bandwidth and calibration accuracy will then be determined, in order to develop better information coding techniques for optimal communication bandwidth (speed) utilization and better subject training and model calibration procedures for best accuracy return on investment of effort. Prototype real-time applications that operate at optimal or near-optimal performance levels utilizing the developed theoretical advancements for communication and control will be implemented, to enable access by and support independence for the target user groups. Project outcomes will disrupt the trend of black-box BCI design by building dynamic system models for stimulus-to-EEG systems encountered in BCI applications, and treating them as stochastic communication channels in order to characterize signals accordingly and to employ information theoretic approaches to analysis and design. This novel theoretical framework will enable model-based quantitative characterization of BCI performance limits and will allow the design of optimal or near-optimal coding/decoding strategies as well as improved calibration procedures that will have immediate impact on increasing bandwidth and intent detection accuracy, as well as calibration duration reduction in BCI systems - primary barriers between laboratory prototypes and real-world-worthy BCI products.Broader Impacts: If successful this project will advance BCI technology to the next level, thereby revolutionizing human computer interaction and empowering persons with physical disabilities by enabling seamless control of computers and devices. The project will afford, through collaboration with the Center for Subsurface Sensing and Imaging Systems (CenSSIS) at Northeastern University as well as colleagues across departments and institutions, opportunities to both undergraduate engineering and non-engineering majors for enhanced learning and collaboration skills by immersing them in interdisciplinary cutting-edge research and design projects with societal impact. The PI will engage high school students and teachers in the research through his institution's Center for STEM Education. And he will inform the broader public of ongoing technological advances in the BCI field and raise disability awareness through collaboration with the Cahners ComputerPlace at the Boston Museum of Science.