Construct and Evaluate a Phone Dialing System Leveraging SSVEP Brain-Computer Interface

Jinsha Liu, Boning Li, Jianting Cao
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Abstract

This study presents a SSVEP based BCI system, designed for dialing a phone number through EEG signals. Our SSVEP system leverages a tablet-based stimulator and OpenBCI Cyton board, employing Canonical Correlation Analysis for EEG signal classification. Tested on 7 participants, the system demonstrated a high accuracy rate of 98.1% in identifying the observed keys. The use of a tablet-based SSVEP stimulator was found to reduce visual fatigue compared to traditional LED stimulators. Despite its initial success, further validation with a larger cohort and in varied real-world conditions is required. This work signifies a promising advancement in utilizing BCIs in practical applications.
利用 SSVEP 脑机接口构建和评估电话拨号系统
本研究介绍了一种基于 SSVEP 的生物识别(BCI)系统,旨在通过脑电信号拨打电话号码。我们的 SSVEP 系统利用基于平板电脑的刺激器和 OpenBCI Cyton 板,并采用 Canonical Correlation Analysis 进行脑电信号分类。该系统对 7 名参与者进行了测试,在识别观察到的按键方面,准确率高达 98.1%。与传统的 LED 刺激器相比,使用基于平板电脑的 SSVEP 刺激器可减轻视觉疲劳。尽管该系统取得了初步成功,但还需要在更大的群体和各种实际条件下进行进一步验证。这项工作标志着在实际应用中使用生物识别技术取得了可喜的进展。
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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