EEG Data Fusion for Improving Accuracy of Binary Classification

被引：0

作者：

Skarga-Bandurova, Inna ^{[1
]}

Biloborodova, Tetiana ^{[1
]}

Skarha-Bandurov, Illia ^{[2
]}

Zagorodna, Natalia ^{[3
]}

Shumova, Larisa ^{[1
]}

机构：

[1] Volodymyr Dahl East Ukrainian Natl Univ, Lugansk, Luhansk Oblast, Ukraine

[2] Luhansk State Med Univ, Lugansk, Luhansk Oblast, Ukraine

[3] Ternopil Ivan Puluj Natl Tech Univ, Ternopol, Ternopil Oblast, Ukraine

来源：

ICT FOR HEALTH SCIENCE RESEARCH | 2019年 / 258卷

关键词：

EEG; data fusion; classification; technique;

D O I：

10.3233/978-1-61499-959-1-130

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper refers to the problem of classification for multiple medical data. The proposed methodology for EEG data processing consists of seven stages and assumes different variations of the Dempster-Shafer technique as a base instrument for data fusion. Attained accuracy is comparable to other more popular algorithms and can be a promising further basis for real-time data classification.

引用

页码：130 / 134

页数：5

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