Alan P Pinheiro1, Maria Eugênia Dajer2, Adriana Hachiya2, Arlindo N Montagnoli3, Domingos Tsuji2. 1. Nucleus of Scientific and Technological Development, Faculty of Electrical Engineering, Federal University of Uberlândia, Patos de Minas, Brazil. Electronic address: alan@eletrica.ufu.br. 2. School of Medicine, University of São Paulo, São Paulo, Brazil. 3. Department of Electrical Engineering, Federal University of São Carlos, São Carlos, Brazil.
Abstract
OBJECTIVE: To characterize the voice and vocal fold function of an individual, it is essential to evaluate vocal fold vibration. The most widely used method for this purpose has been videolaryngoscopy. METHODS: This article proposes a digital image processing algorithm to estimate the glottal area (ie, the space between the vocal folds) and produce graphs of the opening and closing phases of the glottal cycle. In eight subjects without voice disorders, vocal fold movements were recorded by high-speed videolaryngoscopy at 4000 frames per second. The video data were processed by a combination of image segmentation techniques that estimate the glottal area. The segmented area was used to construct the glottal waveform. RESULTS: The graphs revealed important properties of vocal fold vibration, including amplitude, velocity, and other characteristics that have a major influence on voice quality. CONCLUSIONS: The combination of the high-speed technology with the proposed method improves the vocal fold analysis given a numerical feedback through graphical representation of the real vibratory patterns of the folds.
OBJECTIVE: To characterize the voice and vocal fold function of an individual, it is essential to evaluate vocal fold vibration. The most widely used method for this purpose has been videolaryngoscopy. METHODS: This article proposes a digital image processing algorithm to estimate the glottal area (ie, the space between the vocal folds) and produce graphs of the opening and closing phases of the glottal cycle. In eight subjects without voice disorders, vocal fold movements were recorded by high-speed videolaryngoscopy at 4000 frames per second. The video data were processed by a combination of image segmentation techniques that estimate the glottal area. The segmented area was used to construct the glottal waveform. RESULTS: The graphs revealed important properties of vocal fold vibration, including amplitude, velocity, and other characteristics that have a major influence on voice quality. CONCLUSIONS: The combination of the high-speed technology with the proposed method improves the vocal fold analysis given a numerical feedback through graphical representation of the real vibratory patterns of the folds.