Implementation of a Classification System of EEG Signals Based on FPGA

被引：0

作者：

Asanza, Victor ^{[1
]}

Constantine, Alisson ^{[1
]}

Valarezo, Stephany ^{[1
]}

Pelaez, Enrique ^{[1
]}

机构：

[1] Escuela Super Politecn Litoral ESPOL, Fac Ingn Elect & Comp, Guayaquil, Ecuador

来源：

2020 SEVENTH INTERNATIONAL CONFERENCE ON EDEMOCRACY & EGOVERNMENT (ICEDEG) | 2020年

关键词：

Neural Networks; Electroencephalography; Embedded Systems; FPGA; Pattern Recognition;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In the field of prosthetics, different technologies have been incorporated in recent years to improve their development and control, likewise the application of Field-Programmable Gate Arrays (FPGA) related to the Biomedicine field has increased due to its flexibility to perform multiple instructions in a reduced amount of time. This paper presents the implementation of a classification system based on FPGA capable of classifying characterized data, representing an imaginary motor task and a motor task in lower extremities. A three-layer feed-forward neural network was designed in Matlab, testing different architectures to assess the performance of the classifier, using methods such as the confusion matrix and the ROC curve.

引用

页码：87 / 92

页数：6

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