Visualization and Analysis of Vocal Fold Dynamics in Various Voice Disorders

B Panchami; S Pravin Kumar; Ketaki Vasant Phadke

doi:10.1016/j.jvoice.2024.03.035

Visualization and Analysis of Vocal Fold Dynamics in Various Voice Disorders

J Voice. 2024 May 8:S0892-1997(24)00113-9. doi: 10.1016/j.jvoice.2024.03.035. Online ahead of print.

Authors

B Panchami¹, S Pravin Kumar², Ketaki Vasant Phadke³

Affiliations

¹ Department of Biomedical Engineering, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Tamil Nadu, India. Electronic address: panchamib@ssn.edu.in.
² Department of Biomedical Engineering, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Tamil Nadu, India. Electronic address: pravinkumars@ssn.edu.in.
³ The Voice Wellness Centre, A Unit of Macrocosmos Creations Pvt Ltd, Bengaluru, Karnataka, India. Electronic address: ketakislp@gmail.com.

PMID: 38724310
DOI: 10.1016/j.jvoice.2024.03.035

Abstract

Objectives/hypothesis: This study aims to compare the glottal dynamics of vocal fold leukoplakia, laryngitis, and papilloma using various visualization techniques, including phonovibrograms (PVG) and glottovibrograms (GVG). It hypothesizes that these techniques can provide understanding of the vibratory dynamics of these voice disorders, which can aid in their objective diagnosis and deriving visual features for computer-assisted classifications.

Study design: This work employs a comparative analysis of vocal fold disorders using visualization techniques. The study examines PVG, derivative of PVG (PVG-1), digital kymograms (DKG), and GVG to analyze the glottal dynamics of vocal fold leukoplakia, laryngitis, and papilloma.

Methods: The study utilizes high-speed video endoscopy to capture vocal fold behavior in different pathological conditions. PVG, GVG, and DKG techniques are applied to visualize and analyze the vibratory patterns of the vocal folds. PVG offers a comprehensive portrayal of vocal fold motion, while GVG presents the distance between vocal fold contours. The study also examines PVG-1 as a derivative of PVG.

Results: Distinct modifications in vocal fold vibrations across various stages (open, closed, closing, and opening) are documented using PVG, PVG-1, GVG, DKG, and PVG trajectory. Healthy vocal folds exhibit consistent periodic patterns, while disorders, such as leukoplakia, laryngitis, and papilloma, manifest unique features due to structural and functional variations. The methods employed identify both structural irregularities and functional deviations in vocal fold vibrations.

Conclusions: Comparative analyses using PVG and other visualization techniques aid in understanding the glottal dynamics of voice disorders. While laryngoscopy and stroboscopy are valuable for real-time assessment, offline analysis techniques, such as PVG and GVG, are useful for tracking glottal dynamics during phonation and assessing treatment effectiveness over time. Studies like this will contribute to standardizing the PVG-based diagnostic criteria for its clinical utility, and development of classification tools for improved diagnosis and management of vocal fold pathologies.

Keywords: Digital kymograms; Glottovibrograms; Laryngeal dynamics; Phonovibrograms; Visualization.