脑服:实现集成脑电图的多模式服装

J. F. Vargas, Bo Zhou, Hymalai Bello, P. Lukowicz
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引用次数: 2

摘要

我们的目标是通过开发具有最先进模拟前端的开源脑电图传感模块,促进脑电图传感在多模式智能服装中的广泛应用,该模块的引脚/协议与可穿戴和 DIY 社区中流行的生态系统兼容。脑电图功能通过神经科学标准 n-back 记忆负载任务进行了验证。我们还演示了将脑电图电极与低频力敏电阻器(FSR)和高频压电传感器无缝集成在一个探头中。最后,我们展示了将整个装置嵌入纺织棒球帽的过程。我们还介绍了在运动伪影和不同活动等情况下,不同模态的信号如何通过一件不显眼的头戴式服装相互补充。该系统通过 GitHub 公共存储库向社区开放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brainwear: Towards Multi-modal Garment Integrated EEG
We aim to facilitate broad use of EEG sensing in multi-modal smart garments by developing an open-source EEG sensing module with the state-of-the-art analog front-end that is pin/protocol-compatible with popular ecosystems in the wearable and DIY community. The EEG functionality is validated with the neuroscience standard n-back memory load task. We also demonstrate the seamless integration of EEG electrodes with low-frequency Force Sensitive Resistors (FSR) and high-frequency piezoelectric sensors within a single probe. Finally, we show the embedding of the entire setup in a textile baseball cap. We also present how signals from the different modalities complement each other under situations such as motion artifacts and different activities from an unobtrusive head-worn garment. The system is available to the community through a public GitHub repository.
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