Basic Hand Gestures Classification Based on Surface Electromyography

被引：15

作者：

Palkowski, Aleksander ^{[1
]}

Redlarski, Grzegorz ^{[1
]}

机构：

[1] Gdansk Univ Technol, Dept Mechatron & High Voltage Engn, Ul G Narutowicza 11-12, PL-80233 Gdansk, Poland

来源：

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE | 2016年 / 2016卷

关键词：

Optimization; -; Electromyography;

D O I：

10.1155/2016/6481282

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average classification rate of 98.12% has been achieved for the proposed method.

引用

页数：7

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