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Wearable ear EEG for brain interfacing

机译:可穿戴式耳式脑电图仪,用于大脑接口

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Brain-computer interfaces (BCIs) measuring electrical activity via electroencephalogram (EEG) have evolved beyond clinical applications to become wireless consumer products. Typically marketed for meditation and neu-rotherapy, these devices are limited in scope and currently too obtrusive to be a ubiquitous wearable. Stemming from recent advancements made in hearing aid technology, wearables have been shrinking to the point that the necessary sensors, circuitry, and batteries can be fit into a small in-ear wearable device. In this work, an ear-EEG device is created with a novel system for artifact removal and signal interpretation. The small, compact, cost-effective, and discreet device is demonstrated against existing consumer electronics in this space for its signal quality, comfort, and usability. A custom mobile application is developed to process raw EEG from each device and display interpreted data to the user. Artifact removal and signal classification is accomplished via a combination of support matrix machines (SMMs) and soft thresholding of relevant statistical properties.
机译:通过脑电图(EEG)来测量电活动的脑机接口(BCI)已经超越临床应用而发展成为无线消费产品。这些设备通常用于冥想和神经疗法,其范围有限,目前过于引人注目,无法普遍使用。由于助听器技术的最新发展,可穿戴设备已经缩小到可以将必要的传感器,电路和电池安装到小型入耳式可穿戴设备中的程度。在这项工作中,创建了带有新颖系统的耳EEG设备,用于去除伪像和信号解释。小型,紧凑,经济高效且谨慎的设备在该领域相对于现有的消费类电子产品展示出其信号质量,舒适性和可用性。开发了自定义移动应用程序,以处理每个设备的原始EEG并将解释的数据显示给用户。伪影去除和信号分类是通过结合支持矩阵机(SMM)和相关统计属性的软阈值来完成的。

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