文章基本信息

标题：Effects of Digital Filtering on the Classification Performance of Steady-State Visual Evoked Potential Based Brain-Computer Interfaces
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作者：Volkan ÇETİN ; Serhat ÖZEKES ; Huseyin Selcuk VAROL 等
期刊名称：Balkan Journal of Electrical & Computer Engineering
印刷版ISSN：2147-284X
出版年度：2020
卷号：8
期号：1
页码：108-113
DOI：10.17694/bajece.654288
语种：English
出版社：Kirklareli University
摘要：The electrical activity that occurs during the communication of neurons is recorded by a method called electroencephalography. Brain computer interfaces utilize various electrophysiological sources obtained from different regions of the brain. The electrophysiological source used in this study is the electrical activity seen in the occipital lobes as a result of visual stimuli that flicker at certain frequencies, and is called steady-state visual evoked potential. The main goal in this work is not to try to improve the classification performance but to investigate the effects of different digital filtering algorithms on classification performance. The effects of the high pass and low pass filtering on the classification performance in steady-state visual evoked potential based brain computer interfaces are investigated. As a result of this study, no significant change in the classification performances of designs with only high pass filtering, and high and low pass filtering, has been observed. In addition, it has been observed that only the designs include a high-pass filter implementation give better classification performance in many cases. Consequently, it is concluded that low-pass filtering in steady-state visual evoked potential based brain-computer interfaces does not provide the desired contribution to classification performance.
关键词：Brain-Computer Interfaces; Machine Learning; Biomedical Signal Processing