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基于硬件的可配置算法，用于使用单通道脑机接口头戴设备检测眨眼信号。

A Hardware-Based Configurable Algorithm for Eye Blink Signal Detection Using a Single-Channel BCI Headset.

机构信息

Departamento de Ingeniería Electrónica Sistemas Informáticos y Automática, Universidad de Huelva, 21007 Huelva, Spain.

Centro Científico Tecnológico de Huelva (CCTH), University of Huelva, 21007 Huelva, Spain.

出版信息

Sensors (Basel). 2023 Jun 5;23(11):5339. doi: 10.3390/s23115339.

DOI:10.3390/s23115339
PMID:37300066
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10255990/
Abstract

Eye blink artifacts in electroencephalographic (EEG) signals have been used in multiple applications as an effective method for human-computer interaction. Hence, an effective and low-cost blinking detection method would be an invaluable aid for the development of this technology. A configurable hardware algorithm, described using hardware description language, for eye blink detection based on EEG signals from a one-channel brain-computer interface (BCI) headset was developed and implemented, showing better performance in terms of effectiveness and detection time than manufacturer-provided software.

摘要

眼动伪迹已被广泛应用于多种脑电图（EEG）信号应用中，是一种有效的人机交互方法。因此，一种有效且低成本的眨眼检测方法对于该技术的发展将是非常有价值的辅助手段。本研究提出了一种基于单通道脑机接口（BCI）头戴设备 EEG 信号的眨眼检测的可配置硬件算法，该算法使用硬件描述语言进行描述，并进行了硬件实现。与制造商提供的软件相比，该算法在有效性和检测时间方面具有更好的性能。

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