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

职业：无创脑接口的信号模型、通道容量和信息率

• 批准号: 1149570
• 负责人: Deniz Erdogmus
• 金额: $ 50.46万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1149570&HistoricalAwards=false
• 关键词: CAREER; Signal; Models; Channel; Capacity

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.

PI的最终研究目标是使有严重语言和身体障碍的人能够独立和富有成效地生活。 为此，他将在该项目中开发和推进新兴的脑机接口（BCI）技术，通过严格开发脑电描记术（EEG）在BCI设计背景下测量的大脑视觉诱发电位（VEP）的宏观动态模型。 这些模型将使BCI的通信信道解释成为可能，并将使信息理论和数字通信概念的应用所产生的分析和设计突破成为可能。 皮质动力学和背景过程将使用概率动态框架在适合BCI分析和设计的时空尺度上建模。 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，以实现最佳通信带宽（速度）利用率，并开发更好的受试者培训和模型校准程序，以实现最佳精度投资回报。 原型实时应用程序，运行在最佳或接近最佳的性能水平，利用开发的理论进步的通信和控制将被实施，使访问和支持独立的目标用户群。 项目成果将打破黑箱BCI设计的趋势，为BCI应用中遇到的刺激-EEG系统建立动态系统模型，并将其视为随机通信通道，以相应地表征信号，并采用信息论方法进行分析和设计。 这种新颖的理论框架将实现BCI性能极限的基于模型的定量表征，并将允许设计最佳或接近最佳的编码/解码策略以及改进的校准程序，这将对增加带宽和意图检测准确性产生直接影响。以及BCI系统中校准持续时间的减少-实验室原型和现实世界之间的主要障碍-更广泛的影响： 如果成功，该项目将把BCI技术推进到一个新的水平，从而彻底改变人机交互，并通过实现对计算机和设备的无缝控制来增强身体残疾人的能力。 该项目将通过与东北大学地下传感和成像系统中心（CenSSIS）以及各部门和机构的同事合作，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力的跨学科前沿研究和设计项目中，增强学习和协作技能。 PI将通过其机构的STEM教育中心让高中学生和教师参与研究。 他还将通过与波士顿科学博物馆的Cahners ComputerPlace合作，向更广泛的公众介绍BCI领域正在取得的技术进步，并提高对残疾人的认识。