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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/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:[電機工程學系暨研究所] 期刊論文

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