School of Artificial Intelligence, Guilin University of Electronic Technology, Guilin 541004, China.
The Laboratory for Imagery, Vision and Artificial Intelligence, Ecole de Technologie Supérieure, Montreal, QC H3C 1K3, Canada.
Sensors (Basel). 2023 Jul 16;23(14):6434. doi: 10.3390/s23146434.
The electroencephalography (EEG) signal is a noninvasive and complex signal that has numerous applications in biomedical fields, including sleep and the brain-computer interface. Given its complexity, researchers have proposed several advanced preprocessing and feature extraction methods to analyze EEG signals. In this study, we analyze a comprehensive review of numerous articles related to EEG signal processing. We searched the major scientific and engineering databases and summarized the results of our findings. Our survey encompassed the entire process of EEG signal processing, from acquisition and pretreatment (denoising) to feature extraction, classification, and application. We present a detailed discussion and comparison of various methods and techniques used for EEG signal processing. Additionally, we identify the current limitations of these techniques and analyze their future development trends. We conclude by offering some suggestions for future research in the field of EEG signal processing.
脑电图(EEG)信号是一种非侵入性的复杂信号,在生物医学领域有许多应用,包括睡眠和脑机接口。鉴于其复杂性,研究人员提出了几种先进的预处理和特征提取方法来分析 EEG 信号。在这项研究中,我们对大量与 EEG 信号处理相关的文章进行了综合回顾。我们搜索了主要的科学和工程数据库,并总结了我们的发现结果。我们的调查涵盖了 EEG 信号处理的整个过程,从采集和预处理(去噪)到特征提取、分类和应用。我们对用于 EEG 信号处理的各种方法和技术进行了详细的讨论和比较。此外,我们还确定了这些技术的当前局限性,并分析了它们未来的发展趋势。最后,我们对 EEG 信号处理领域的未来研究提出了一些建议。