Combining Artificial Intelligence and Automatic Analysis to Study of the Closure Characteristics of Healthy Human Vocal Cords during Phonation Using Synchronous Electroglottography and Laryngeal High-Speed Videoendoscopy

Abstract

Objective: To use an artificial intelligence neural network to automatically analyze images from high-speed videoendoscopy and synchronous electroglottographic signals in healthy vocal folds to obtain the accurate glottal opening and closing instants in the glottal cycle. This method will be compared to the traditional electroglottography point derivation method to explore the glottal opening and closing characteristics of the vocal folds and better interpret the opening and closing instances of the electroglottography.