Real-Time EEG Acquisition System for FPGA-based BCI

被引：2

作者：

Eneriz, Daniel ^{[1
]}

Medrano, Nicolas ^{[1
]}

Calvo, Belen ^{[1
]}

Caren Hernandez-Ruiz, Ana ^{[1
]}

Antolin, Diego ^{[2
]}

机构：

[1] Univ Zaragoza, Aragon Inst Engn Res I3A, Grp Elect Design, Zaragoza, Spain

[2] Univ Zaragoza, La Almunia Politech Sch, Dept Elect, Grp Elect Design, La Almunia De Dona Godin, Spain

来源：

PROCEEDINGS OF THE 37TH CONFERENCE ON DESIGN OF CIRCUITS AND INTEGRATED SYSTEMS (DCIS 2022) | 2022年

关键词：

Electroencephalograph; Brain-Computer Interfaces; Field-Programmable Gate Array; Real-Time Acquisition; MOTOR IMAGERY; CLASSIFICATION;

D O I：

10.1109/DCIS55711.2022.9970028

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Multichannel electroencephalograph (EEG) signals data acquisition is non-invasive and easy to implement, thus being the preferred brain-related information carriers for Brain Computer Interfaces (BCIs). Since BCIs must be capable of processing information in real-time, their implementation in edge devices is currently being boosted, particularly on FieldProgrammable Gate Arrays (FPGA). In this work, a real-time EEG acquisition system based on the XADC of the Xilinx Zynq FPGA is presented, meeting the requirements of a well-known BCI processing algorithm, the EEGNet. Performed tests show minimal error in the acquisition, whose effects in the EEGNet accuracy are negligible.

引用

页码：65 / 69

页数：5

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