CHS: Small: Auditory and Haptic Based Brain-Computer Interfaces Using In-Ear Electrodes

脑机接口(BCI)是允许人们仅通过大脑信号来控制计算机和其他设备的系统。BCI有可能改善许多严重肢体残疾的人的生活，允许他们在不需要肌肉运动或语音的情况下进行交流和控制环境。经过二十多年的研究，BCI已经变得足够强大和可靠，可以考虑将其用于主流应用，例如设备的免提和免语音控制。然而，最常见的BCI需要视觉注意力，这限制了它们对有视觉障碍的人或在转移视觉注意力是危险的或不可能的移动环境(如驾驶)的使用。视觉显示的有趣替代品是基于听觉(声音)或触觉(触摸或感觉，如振动)的BCI界面，或者是这些界面的组合的多模式BCI界面。除了为视力障碍或特殊目的的人提供替代界面外，设备的非视觉BCI控制在日常生活中也可能有用，例如在电影院回复短信时，不看设备屏幕或说话。这个项目将通过发展听觉、触觉和多模式刺激的知识体系来扩展BCI的最先进水平，这些都是该领域相对未被探索的领域。此外，这项研究将创造和探索用于检测大脑信号的小型可穿戴耳内电极，从而为新兴的移动BCI领域做出贡献，这将为大量主流用户打开可能性。目前的脑-机接口系统涵盖了各种各样的大脑信号和记录技术；这项研究集中在“诱发反应”脑电图仪(EEG)方法上，也就是说，大脑信号是由于声音、闪光或触摸等刺激而触发的。为此，该项目将研究听觉和触觉提示，以确定将它们映射到输入选择的最佳方式。听觉和触觉接口的最大挑战之一是如何标记刺激，使其对BCI用户有意义。为了解决这个问题，该项目将探索将听觉和触觉刺激的标记和映射编码为刺激本身的新方法(以类似于标记视觉刺激的方式，例如当目标是闪烁的字母时，这样用户可以通过查看来确定提示的含义)。他们的计划是利用发声方面的研究(主要集中于在听觉“显示”中呈现数据)，设计出将语音或模式音调(如莫尔斯电码)编码成音频提示的技术，以便用户只需听提示就能确定其含义。该团队还将试验各种多模式方法(将视觉、听觉和触觉线索结合在一个系统中)，以实现比单独使用单一刺激模式更高的准确性。最后，该项目将评估耳内EEG电极在检测大脑对听觉和触觉刺激的反应方面的有效性，试验电极设计、耳朵内放置以及各种过滤器和分类器以提高信噪比。替代刺激的实验结果将与优化的可穿戴电极系统相结合，为主流用户创造首个免提、无语音、无视觉的界面。

Brain Computer Interfaces (BCIs) are systems that allow people to control computers and other devices with brain signals alone. BCIs have the potential to improve the lives of many individuals with severe physical disabilities, by allowing them to communicate and control their environment without needing muscle movement or voice. After more than two decades of research, BCIs have become robust and reliable enough to consider them for mainstream applications, such as hands-free and voice-free control of devices. However, the most common BCIs require visual attention, which restricts their utility for people with visual impairments, or for mobile environments (such as driving) where diverting visual attention is dangerous or not possible. Intriguing alternatives to visual displays are auditory (sounds) or haptic (touch or sensations such as vibrations) based BCI interfaces, or multimodal BCI interfaces which are a combination of these. In addition to providing an alternate interface for people with visual impairments or for special purposes, nonvisual BCI control of devices could also be useful in everyday life, such as when responding to a text message in a movie theater without looking at a device screen or speaking. This project will extend the state of the art in BCIs by evolving the body of knowledge in auditory, haptic, and multimodal stimuli, which are relatively unexplored areas of the field. Additionally, the research will create and explore small, wearable in-ear electrodes to detect brain signals, and thus will contribute to the emerging field of mobile BCIs which will open possibilities for large numbers of mainstream users. Current BCI systems cover a wide and varying range of brain signals and recording technologies; this research focuses on "evoked-response" electroencephalograph (EEG) approaches, that is to say brain signals that are triggered due to a stimulus such as a sound, flashing light, or touch.To these ends, the project will study auditory and haptic cues to determine the best ways to map them to input choices. One of the biggest challenges with auditory and haptic interfaces is how to label a stimulus so it is meaningful to the BCI user. To address this problem, the project will explore novel methods of encoding the labeling and mapping of auditory and haptic stimuli into the stimuli themselves (in a manner analogous to how it is possible to label visual stimuli, such as when the target is a flashing letter so the user can determine the meaning of a cue by looking at it). The plan is to leverage research in sonification (which largely focuses on presenting data in auditory "displays") to devise techniques for encoding speech or patterned tones (such as Morse code) into audio cues in such a way that a user can simply listen to the cue to determine its meaning. The team will also experiment with a variety of multimodal approaches (combining visual, auditory, and haptic cues in a single system) in order to achieve higher accuracy than is possible with a single stimulus mode alone. Finally, the project will evaluate the effectiveness of in-ear EEG electrodes in detecting brain responses to auditory and haptic stimuli, experimenting with electrode design, placement within the ear, and various filters and classifiers to improve the signal-to-noise ratio. The results of the experiments in alternative stimuli will be combined with the optimized wearable electrode system, to create the first hands-free, voice-free, vision-free interfaces for mainstream users.