Integrated analyzer and classifier of glottographic signals

Electroglottography (EGG) and photoglottography (PGG) are two plausible methods to study voice production for monitoring the patterns of laryngeal vibrations. It has been suggested that measures such as open quotient and speed quotient calculated from glottographic signals can provide useful information regarding pathological phonation. In this paper, an integrated analyzer and classifier of glottographic signals was implemented. The system makes it possible to calculate the measures from digitized EGG and PGG signals automatically in order to examine vocal fold abnormality. The system developed several techniques to extract features from glottographic signals and proposed a statistical classification method that can possibly aid the diagnosis process. To check the reliability of the system, a training set and a test set of glottographic signals from normal people and patients with recurrent/superior laryngeal paralysis were analyzed and classified by the system. The results showed that the system is a useful tool for quantitative study of phonatory pathophysiology and can be used by the examiner who is interested in the clinical examination of glottographic signals. Moreover, glottographic techniques may have some clinical applications in the quantitative documentation of phonatory function in patients with voice disorders but requires further evaluation before clinical application.