General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2012 Vol.4(6): 967-970 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2012.V4.617

Automatic Recognition of Finger Gestures Using a Tri-Axis Accelerometer

Yinghui Zhou, Lei Jing, and Zixue Cheng

Abstract—More and more researchers devote themselves to system development of life support for elders such as health condition monitoring, appliances control, emergency call, and so on. Activity recognition using wearable devices is one of the ways of system implementation. In this paper, a system of gesture recognition is designed and implemented based on a tri-axis accelerometer. Six pairs of one-stroke finger gestures are defined according to the sensing characteristic of the accelerometer. Acceleration data was collected from 20 subjects under the supervision by researchers. Gesture information was segmented automatically from successive time signal. Mean, standard deviation, and the relationship of position sequence of wave crest and trough are extracted as features for training and testing of gestures classifying. Several classifiers were selected for gestures recognition. Results show the KNN classifier got the best recognizing result with an average accuracy of 91.58%. The recognition rate is not influenced by which hand being used to perform the gestures.

Index Terms—Wearable computing, gesture recognition, accelerometer, short time energy

The authors are with the Graduate School of Computer Science and Engineering, University of Aizu, Aizu-Wakamatsu, 965-8580, Japan (e-mail: d8131104@u-aizu.ac.jp, leijing@u-aizu.ac.jp, z-cheng@u-aizu.ac.jp).

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Cite: Yinghui Zhou, Lei Jing, and Zixue Cheng, "Automatic Recognition of Finger Gestures Using a Tri-Axis Accelerometer," International Journal of Computer Theory and Engineering vol. 4, no. 6, pp. 967-970, 2012.


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