CHS: Small: A Novel P300 Brain-Computer Interface

CHS：小型：新型 P300 脑机接口

• 批准号: 1528214
• 负责人: Virginia de Sa
• 金额: $ 49.96万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1528214&HistoricalAwards=false
• 关键词: CHS; Small; Novel; P300; Brain; CHS; Small; Novel; P300; Brain

Brain computer interfaces (BCIs) translate basic mental commands into computer-mediated actions, thereby allowing the user to bypass the peripheral motor system and interact with the world directly via brain activity. These systems are being developed to aid users with motor deficits stemming from neurodegenerative disease, injury, or even environmental restrictions which make movement difficult or impossible. One of the most successful classes of EEG-driven BCI systems is the P300, which works by detecting user responses to flashed stimuli. In most P300 systems, a grid of letters and/or other symbols is presented and rows or columns of the symbols are flashed in random order; the user attends to the desired symbol (usually by silently counting when it flashes). A major problem with these grid-based P300 systems is that the user must ideally look at the flashed target and minimally attend to the tiny letters, but late-stage ALS and other locked-in patients for whom these systems are most needed have trouble foveating targets and making controlled eye movements. The PI's hypothesis is that a BCI that flashes segments of one large letter can retain the combinatorial efficiency that comes with querying several letters at once, while having the advantage of one central focus (no gaze shifts required). This research aims to design and test this new segment speller idea. Project outcomes have the potential to vastly improve the usability of P300 EEG-based BCI systems for those with visual, sensory and motor impairments. All software written for EEG signal processing and analysis will be made available as add-ons to EEGLAB which is distributed by the Swartz Center for Computational Neuroscience (SCCN) at UCSD and part of the Temporal Dynamics of Learning Center. Data will also be made available through the HeadIT data archive that is also run by the SCCN.This research task can be broken down into three main objectives: develop and test the response to flashed segments; improve the single-trial classification of the responses to flashed segments; and design a logic for selecting segments and interpreting their responses. The developed system will provide another method for BCI speller control that does not depend on the ability to shift gaze. The PI argues that this method will have a higher information transfer rate than other space invariant BCI spellers due to being able to probe multiple letters at once. Besides being advantageous for those with impaired eye movements and/or impaired vision, the method should have other advantages over the standard P300 systems. When errors are made, they will tend to be to visually similar symbols. Incorporating language priors and active segment selection is easily accommodated, and this may result in higher information transfer rates with slower flash rates. In addition the work on improving recognition of single-trial temporal EEG signals and incorporating Bayesian language models into spellers could be useful for other types of brain-computer interfaces.

大脑计算机接口（BCIS）将基本的心理命令转化为计算机介导的动作，从而使用户绕过外围运动系统并通过大脑活动直接与世界互动。 这些系统的开发是为了帮助使用神经退行性疾病，伤害甚至环境限制的运动缺陷的用户，这使运动变得困难或不可能。 p300是最成功的EEG驱动的BCI系统之一，它通过检测用户对闪烁刺激的响应而起作用。 在大多数P300系统中，都会呈现字母和/或其他符号的网格，并以随机顺序闪烁符号的行或列；用户关注所需的符号（通常是在闪烁时静静地计数）。 这些基于网格的P300系统的一个主要问题是，用户必须理想地看一下闪烁的目标，并最少地参加小字母，但是后期ALS和其他最需要的系统最需要的锁定患者遇到了困难的目标并进行了受控的眼球运动。 PI的假设是，闪烁一个大字母段的BCI可以保留一次查询几个字母的组合效率，同时具有一个中心焦点的优势（无需凝视转移）。 这项研究旨在设计和测试这个新的拼写拼写想法。 项目成果有可能大大提高具有视觉，感觉和运动障碍的人的基于p300 EEG的BCI系统的可用性。 所有用于EEG信号处理和分析的软件将作为EEGLAB的附加组件提供，该附件由UCSD的Swartz计算神经科学中心（SCCN）和学习中心的时间动态分布。 还将通过SCCN运行的Headit Data Archive提供数据。该研究任务可以分解为三个主要目标：开发和测试对闪烁片段的响应；改善对闪烁段的响应的单审判分类；并设计一种用于选择细分并解释其响应的逻辑。 开发的系统将为BCI拼写控制提供另一种方法，该方法不取决于转移凝视的能力。 PI认为，由于能够一次探测多个字母，因此该方法的信息传输速率将比其他空间不变的BCI拼写率更高。 除了对眼睛运动受损和/或视力受损的人有利外，该方法还应比标准P300系统具有其他优势。 发生错误时，它们将倾向于在视觉上类似的符号。将语言先验和主动段选择纳入容易，这可能会导致较高的信息传输速率以较慢的闪存速率。 此外，改善单次临时脑电图信号并将贝叶斯语言模型纳入拼写的工作可能对其他类型的脑部计算机接口有用。