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脑穿戴设备:耳级 EEG 传感器的验证工具包。

Brain Wearables: Validation Toolkit for Ear-Level EEG Sensors.

机构信息

Department of Physics, NOVA School of Science and Technology, 2829-516 Caparica, Portugal.

Segotia, H91 HE9E Galway, Ireland.

出版信息

Sensors (Basel). 2024 Feb 15;24(4):1226. doi: 10.3390/s24041226.

Abstract

EEG-enabled earbuds represent a promising frontier in brain activity monitoring beyond traditional laboratory testing. Their discrete form factor and proximity to the brain make them the ideal candidate for the first generation of discrete non-invasive brain-computer interfaces (BCIs). However, this new technology will require comprehensive characterization before we see widespread consumer and health-related usage. To address this need, we developed a validation toolkit that aims to facilitate and expand the assessment of ear-EEG devices. The first component of this toolkit is a desktop application ("EaR-P Lab") that controls several EEG validation paradigms. This application uses the Lab Streaming Layer (LSL) protocol, making it compatible with most current EEG systems. The second element of the toolkit introduces an adaptation of the phantom evaluation concept to the domain of ear-EEGs. Specifically, it utilizes 3D scans of the test subjects' ears to simulate typical EEG activity around and inside the ear, allowing for controlled assessment of different ear-EEG form factors and sensor configurations. Each of the EEG paradigms were validated using wet-electrode ear-EEG recordings and benchmarked against scalp-EEG measurements. The ear-EEG phantom was successful in acquiring performance metrics for hardware characterization, revealing differences in performance based on electrode location. This information was leveraged to optimize the electrode reference configuration, resulting in increased auditory steady-state response (ASSR) power. Through this work, an ear-EEG evaluation toolkit is made available with the intention to facilitate the systematic assessment of novel ear-EEG devices from hardware to neural signal acquisition.

摘要

基于脑电图(EEG)的耳机代表了脑活动监测领域的一个有前途的前沿领域,超越了传统的实验室测试。它们离散的形式因子和靠近大脑的位置使它们成为第一代离散的非侵入式脑机接口(BCI)的理想选择。然而,这种新技术需要进行全面的特征描述,然后我们才能看到广泛的消费者和与健康相关的使用。为了满足这一需求,我们开发了一个验证工具包,旨在促进和扩展对耳内 EEG 设备的评估。该工具包的第一个组件是一个桌面应用程序(“EaR-P Lab”),它可以控制几个 EEG 验证范例。该应用程序使用实验室流媒体层(LSL)协议,使其与大多数当前的 EEG 系统兼容。工具包的第二个元素引入了一种将幽灵评估概念应用于耳内 EEG 领域的方法。具体来说,它利用测试对象耳朵的 3D 扫描来模拟耳内和周围的典型 EEG 活动,从而可以对不同的耳内 EEG 形式因子和传感器配置进行受控评估。每个 EEG 范例都使用湿电极的耳内 EEG 记录进行了验证,并与头皮 EEG 测量进行了基准测试。耳内 EEG 幽灵成功地获取了硬件特性化的性能指标,根据电极位置揭示了性能差异。利用这些信息优化了电极参考配置,从而提高了听觉稳态响应(ASSR)的功率。通过这项工作,提供了一个耳内 EEG 评估工具包,旨在促进对从硬件到神经信号采集的新型耳内 EEG 设备的系统评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8d7/10893377/b5fd74ae0e4e/sensors-24-01226-g005.jpg

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