Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps

Vikas Mittal, R. K. Sharma

Source Title: International Journal of E-Health and Medical Communications (IJEHMC)12(4)

ISSN: 1947-315X|EISSN: 1947-3168|EISBN13: 9781799861577|DOI: 10.4018/IJEHMC.20210701.oa6

MLA

Mittal, Vikas, and R. K. Sharma. "Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps." IJEHMC vol.12, no.4 2021: pp.97-119. http://doi.org/10.4018/IJEHMC.20210701.oa6

APA

Mittal, V. & Sharma, R. K. (2021). Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps. International Journal of E-Health and Medical Communications (IJEHMC), 12(4), 97-119. http://doi.org/10.4018/IJEHMC.20210701.oa6

Chicago

Mittal, Vikas, and R. K. Sharma. "Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps," International Journal of E-Health and Medical Communications (IJEHMC) 12, no.4: 97-119. http://doi.org/10.4018/IJEHMC.20210701.oa6

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Abstract

The detection and description of pathological voice are the most important applications of voice profiling. Currently, techniques like laryngostroboscopy or surgical microlarynoscopy are popularly used for the diagnosis of voice pathologies but are invasive in nature. Disorders of vocal folds impact the quality of voice, and therefore, the accuracy of voice profiling is reduced. This paper presents a better solution to differentiate normal and pathological voices based on the glottal, physical, and acoustic and equivalent electrical parameters. These parameters have been correlated using mathematical equations and models. Results reveal that the glottal flow is strongly influenced by physical parameters like stiffness and viscosity of vocal folds in case of pathological voice. However, their direct measurement requires complex invasive medical procedures or costly and complex electronic hardware arrangements in case of non-invasive methods. Glottal parameters, on the other hand, facilitate much simpler estimation of vocal folds disorders. In this work, the authors have presented two non-invasive approaches for better accuracy and least complexity for differentiating normal and pathological voices: 1) by using correlation of glottal and physical parameters, 2)by using acoustic and equivalent electrical parameters.