[Performance evaluation of a wearable steady-state visual evoked potential based brain-computer interface in real-life scenario].

Q4 Medicine
Xiaodong Li, Xiang Cao, Junlin Wang, Weijie Zhu, Yong Huang, Feng Wan, Yong Hu
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引用次数: 0

Abstract

Brain-computer interface (BCI) has high application value in the field of healthcare. However, in practical clinical applications, convenience and system performance should be considered in the use of BCI. Wearable BCIs are generally with high convenience, but their performance in real-life scenario needs to be evaluated. This study proposed a wearable steady-state visual evoked potential (SSVEP)-based BCI system equipped with a small-sized electroencephalogram (EEG) collector and a high-performance training-free decoding algorithm. Ten healthy subjects participated in the test of BCI system under simplified experimental preparation. The results showed that the average classification accuracy of this BCI was 94.10% for 40 targets, and there was no significant difference compared to the dataset collected under the laboratory condition. The system achieved a maximum information transfer rate (ITR) of 115.25 bit/min with 8-channel signal and 98.49 bit/min with 4-channel signal, indicating that the 4-channel solution can be used as an option for the few-channel BCI. Overall, this wearable SSVEP-BCI can achieve good performance in real-life scenario, which helps to promote BCI technology in clinical practice.

[基于视觉诱发电位的可穿戴稳态脑机接口在现实场景中的性能评估]。
脑机接口(BCI)在医疗保健领域具有很高的应用价值。但在实际临床应用中,脑机接口的使用应考虑便利性和系统性能。可穿戴式脑机接口的便利性普遍较高,但其在现实场景中的性能有待评估。本研究提出了一种基于稳态视觉诱发电位(SSVEP)的可穿戴脑机接口(BCI)系统,该系统配备了小型脑电图(EEG)采集器和高性能无需训练的解码算法。10名健康受试者在简化实验准备下参与脑机接口系统测试。结果表明,该BCI对40个目标的平均分类准确率为94.10%,与实验室条件下收集的数据集相比无显著差异。系统在8通道信号下的最大信息传输率(ITR)为115.25 bit/min,在4通道信号下的最大信息传输率为98.49 bit/min,表明4通道方案可以作为少通道BCI的一种选择。综上所述,该可穿戴SSVEP-BCI在现实场景中能够取得较好的性能,有助于BCI技术在临床中的推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
生物医学工程学杂志
生物医学工程学杂志 Medicine-Medicine (all)
CiteScore
0.80
自引率
0.00%
发文量
4868
期刊介绍:
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