Classification of Hand Grasp Using Perimeter Change of the Forearm

被引：0

作者：

Choi, Hwiyong ^{[1
]}

Lee, Sangyoon ^{[1
]}

机构：

[1] Konkuk Univ, Dept Mech Design & Prod Engn, Seoul 143701, South Korea

来源：

2012 9TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAL) | 2012年

关键词：

Hand grasp classification; perimeter change of the forearm; Bayesian classification; Strain gauge;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents hand grasp classifier using perimeter change of the forearm. Two sensors based on strain gauge were employed. Signal processing was applied to remove some ripples. Four different classes were trained. Real time classifier was used to recognize the trained grasps. Experimental results show that the average accuracy was 81.2%.

引用

页码：548 / 552

页数：5

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