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  1. Medical and Biological Engineering and Computing
  2. Medical and Biological Engineering and Computing : Volume 49
  3. Medical and Biological Engineering and Computing : Volume 49, Issue 7, July 2011
  4. Voiceless Arabic vowels recognition using facial EMG
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Medical and Biological Engineering and Computing : Volume 55
Medical and Biological Engineering and Computing : Volume 54
Medical and Biological Engineering and Computing : Volume 53
Medical and Biological Engineering and Computing : Volume 52
Medical and Biological Engineering and Computing : Volume 51
Medical and Biological Engineering and Computing : Volume 50
Medical and Biological Engineering and Computing : Volume 49
Medical and Biological Engineering and Computing : Volume 49, Issue 12, December 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 11, November 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 10, October 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 9, September 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 8, August 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 7, July 2011
Effectiveness of medical equipment donations to improve health systems: how much medical equipment is broken in the developing world?
Cardiac regeneration: different cells same goal
Computational analysis of nanoparticle adhesion to endothelium: effects of kinetic rate constants and wall shear rates
Biomechanical modeling of brace treatment of scoliosis: effects of gravitational loads
3D spinal motion analysis during staircase walking using an ambulatory inertial and magnetic sensing system
Predicted effects of pulse width programming in spinal cord stimulation: a mathematical modeling study
Effect of fiducial marker defects on stereotactic target localization in the Leksell stereotactic system
Optimizing bioimpedance measurement configuration for dual-gated nuclear medicine imaging: a sensitivity study
Low intensity microwave radiation as modulator of the l-lactate dehydrogenase activity
Impaired gait in ankylosing spondylitis
Voiceless Arabic vowels recognition using facial EMG
Automatic breath-to-breath analysis of nocturnal polysomnographic recordings
Dynamics of insulin action in hypertension: assessment from minimal model interpretation of intravenous glucose tolerance test data
Spatio-temporal alignment of pedobarographic image sequences
Medical and Biological Engineering and Computing : Volume 49, Issue 6, June 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 5, May 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 4, April 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 3, March 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 2, February 2011
Medical and Biological Engineering and Computing : Volume 49, Issue 1, January 2011
Medical and Biological Engineering and Computing : Volume 48
Medical and Biological Engineering and Computing : Volume 47
Medical and Biological Engineering and Computing : Volume 46
Medical and Biological Engineering and Computing : Volume 45
Medical and Biological Engineering and Computing : Volume 44
Medical and Biological Engineering and Computing : Volume 43
Medical and Biological Engineering and Computing : Volume 42
Medical and Biological Engineering and Computing : Volume 41
Medical and Biological Engineering and Computing : Volume 40
Medical and Biological Engineering and Computing : Volume 39
Medical and Biological Engineering and Computing : Volume 38
Medical and Biological Engineering and Computing : Volume 37
Medical and Biological Engineering and Computing : Volume 36
Medical and Biological Engineering and Computing : Volume 35

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Voiceless Arabic vowels recognition using facial EMG

Content Provider SpringerLink
Author Fraiwan, Luay Lweesy, Khaldon Al Nemrawi, Ayat Addabass, Sondos Saifan, Rasha
Copyright Year 2011
Abstract This work attempts to recognize the Arabic vowels based on facial electromyograph (EMG) signals, to be used for people with speech impairment and for human computer interface. Vowels were selected since they are the most difficult letters to recognize by people in Arabic language. Twenty subjects (7 females and 13 males) were asked to pronounce three Arabic vowels continuously in a random order. Facial EMG signals were recorded over three channels from the three main facial muscles that are responsible for speech. The EMG signals are then pre-processed to eliminate noise and interference signals. Segmentation procedure was implemented to extract the time event that corresponds to each vowel based on a moving standard deviation window. The accuracy of the segmentation procedure was found to be 94%. The recognition of the vowels was carried out by extracting features from the EMG in three domains: the temporal, the spectral, and the time frequency using the wavelet packet transform. Classification of the extracted features was then finally performed using different classification methods implemented in the WEKA software. The random forest classifier with time frequency features showed the best performance with an accuracy of 77% evaluated using a 10-fold cross-validation.
Starting Page 811
Ending Page 818
Page Count 8
File Format PDF
ISSN 01400118
Journal Medical and Biological Engineering and Computing
Volume Number 49
Issue Number 7
e-ISSN 17410444
Language English
Publisher Springer-Verlag
Publisher Date 2011-03-16
Publisher Place Berlin, Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Facial EMG Wavelet packets Feature selection Random forest classifier Biomedical Engineering Human Physiology Computer Applications Imaging Radiology
Content Type Text
Resource Type Article
Subject Biomedical Engineering Computer Science Applications
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