Electroglottographic signal acquisition and neural network based classification for pathology

S. G. Nayak, Jagdish Nayak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The method is used to register the laryngeal behavior indirectly by measuring change in the electrical impedance across the throat during speak or voice. The RF carrier signal is amplitude modulated by the modulating speech/ voice signal and the dc component from the demodulated signal is extracted. The variations in the dc component corresponds to the vocal fold abduction/laryngeal movement. For normal and pathology conditions the results are recorded. These values form a feature vector which reveal information regarding pathology. Then a classical multilayer feed forward neural network with back propagation algorithm is employed to serve as a classifier of the feature vector, giving 100% successful results for the specific data set considered.

Original languageEnglish
Title of host publication3rd Kuala Lumpur International Conference on Biomedical Engineering 2006
PublisherSpringer Verlag
Pages59-62
Number of pages4
Volume15
ISBN (Electronic)9783540680161
Publication statusPublished - 2007
Event3rd Kuala Lumpur International Conference on Biomedical Engineering, Biomed 2006 - Kuala Lumpur, Malaysia
Duration: 11-12-200614-12-2006

Conference

Conference3rd Kuala Lumpur International Conference on Biomedical Engineering, Biomed 2006
CountryMalaysia
CityKuala Lumpur
Period11-12-0614-12-06

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Bioengineering

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  • Cite this

    Nayak, S. G., & Nayak, J. (2007). Electroglottographic signal acquisition and neural network based classification for pathology. In 3rd Kuala Lumpur International Conference on Biomedical Engineering 2006 (Vol. 15, pp. 59-62). Springer Verlag.