• Jan 04, 2024 News!IJFCC will adopt Article-by-Article Work Flow
  • Aug 10, 2026 News!Vol.15, No.2 has been published with online version.   [Click]
  • Mar 30, 2026 News!Vol.15, No.1 has been published with online version.   [Click]
General Information
    • ISSN: 2010-3751 (Print)
    • Frequency: Semi-annual
    • DOI: 10.18178/IJFCC
    • Editor-in-Chief: Prof. Pascal Lorenz
    • Executive Editor: Ms. Fanny Fang
    • Abstracting/ Indexing: Crossref, Electronic Journals Library, Google Scholar, EBSCO, etc.
    • E-mail:  editor@ijfcc.org
    • Article Processing Charge: 500 USD
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the Editor-in-Chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2012 Vol.1(3): 312-315
doi: 10.7763/IJFCC.2012.V1.84

The Performance of Eyes and Hand Gesture Translation to Control Body Turn for Paralyzed Patients

Pimpisa Chankumsri , Waranee Chokanunt , Nunnapad Toadithep

  • Department of Computing, Faculty of Science, Silpakorn University, Nakhon Pathom.

Abstract

This research aims to use the technology of image processing for assisting the Paralyzed Patients to change their posture on bed: turn left, turn right and at the center. Using the patient’s organ that do not paralyzed: fingers and eyes. The picture of actions is captured from web camera, if detect the starting sign, the processes of interpreting the meaning of fingers or eyes are performed. The main principle of fingers detection is, take the input image and subtract from background image, and using the contour algorithm for counting the number of fingers: one, two, and three. In the case of interpreting from the action from eyes, firstly must detect face of patients, using Haar-Like features, and then using Hough Transform for detecting the eye-pupil and interpreting the result. On testing cases of 5 persons, 10 times action for each. We found that, the percentage of accuracy of hand actions is 95.33, the percentage of accuracy of eyes actions is 94.67.

Keywords

  • Haar-like feature
  • finger
  • eyes
  • paralyzed patients
  • body turn
84-V20004

How to Cite

Copied

Pimpisa Chankumsri, Waranee Chokanunt, and Nunnapad Toadithep, "The Performance of Eyes and Hand Gesture Translation to Control Body Turn for Paralyzed Patients," International Journal of Future Computer and Communication, vol. 1, no. 3, pp. 312-315, 2012. https://doi.org/ 10.7763/IJFCC.2012.V1.84

Copyright & License

Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Article Metrics in Dimensions

Copyright © 2012-2026. International Journal of Future Computer and Communication. Unless otherwise stated.

E-mail: editor@ijfcc.org