DocumentCode
596492
Title
Classification of hand grasp using perimeter change of the forearm
Author
Hwiyong Choi ; Sangyoon Lee
Author_Institution
Dept. of Mech. Design & Production Eng., Konkuk Univ., Seoul, South Korea
fYear
2012
fDate
26-28 Nov. 2012
Firstpage
548
Lastpage
552
Abstract
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%.
Keywords
biology computing; biomechanics; sensors; signal classification; strain gauges; forearm; grasp recognition; hand grasp classification; ripple; sensor; signal processing; strain gauge; Accuracy; Bayesian methods; Humans; Muscles; Sensors; Strain; Training; Bayesian classification; Hand grasp classification; Strain gauge; perimeter change of the forearm;
fLanguage
English
Publisher
ieee
Conference_Titel
Ubiquitous Robots and Ambient Intelligence (URAI), 2012 9th International Conference on
Conference_Location
Daejeon
Print_ISBN
978-1-4673-3111-1
Electronic_ISBN
978-1-4673-3110-4
Type
conf
DOI
10.1109/URAI.2012.6463071
Filename
6463071
Link To Document