BCI应用的SSVEP信号检测

P. Prasad, R. Swarnkar, K. Prasad, M. Radhakrishnan, Md. Farukh Hashmi, A. Keskar
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引用次数: 6

摘要

稳态视觉诱发电位(SSVEP)是脑机接口(BCI)应用中最常用的信号之一。提出了一种检测三种不同频率(6Hz, 8Hz和15Hz)的SSVEP信号的新方法。该方法使用快速Walsh Hadamard变换(FWHT)进行特征提取,使用朴素贝叶斯分类器(NBC)进行特征分类。该方法中使用的FWHT和NBC算法消耗的内存更少,计算复杂度也更低。该方法执行时间短,适用于实时BCI应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SSVEP Signal Detection for BCI Application
Steady State Visually Evoked Potential (SSVEP) is one of the most popularly used signals in Brain Computer Interface (BCI) applications. A new method to detect SSVEP signals of three different frequencies (6Hz, 8Hz and 15Hz) has been proposed. This method uses Fast Walsh Hadamard Transform (FWHT) for feature extraction and Naive Bayes Classifier (NBC) for feature classification. The algorithms used in the proposed method FWHT and NBC consumes vey less memory and also makes the method less computationally complex. The proposed method also uses less execution time making it suitable for real time BCI application.
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