A Neural-Network-Based Approach to Recognizing 3D Arm Movement

機構典藏 > College of Engineering > Graduate Institute & Department of Electrical Engineering > Journal Article > Item 987654321/60824

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/60824

Title:	A Neural-Network-Based Approach to Recognizing 3D Arm Movement
Authors:	Su, Mu-chang;Zhao, Yu-xiang;Lai, Eugene
Contributors:	淡江大學電機工程學系
Keywords:	assistive technology;human-computer interface;gesture recognition;neural network
Date:	2003-02
Issue Date:	2013-05-31 11:44:03 (UTC+8)
Publisher:	Singapore: World Scientific Publishing Co. Pte. Ltd.
Abstract:	Gesture recognition is needed for a variety of applications. One particular application of gesture-based systems is to implement a speaking aid for the deaf. Among several factors constituting a hand gesture, the arm movement pattern is one of the most challenging features to recognize. In this paper, we propose a neural-network-based approach to recognition of spatio-tempora patterns of nonlinear 3D arm movements. Compared to Hidden-Markov-Model-based methods, the most appealing property of the proposed method is its simplicity. The effectiveness of this method is evaluated by a database consisted of 10 persons.
Relation:	Biomedical Engineering: Applications, Basis and Communications 15(1), pp.17-26
DOI:	10.4015/S1016237203000043
Appears in Collections:	[Graduate Institute & Department of Electrical Engineering] Journal Article

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