Nonlinear detection of disordered voice productions from short time series based on a Volterra–Wiener–Korenberg model

In this paper, we apply the Volterra–Wiener–Korenberg (VWK) model method to detect nonlinearity in disordered voice productions. The VWK method effectively describes the nonlinearity of a third-order nonlinear map. It allows for the analysis of short and noisy data sets. The extracted VWK model parameters show an agreement with the original nonlinear map parameters. Furthermore, the VWK mode method is applied to successfully assess the nonlinearity of a biomechanical voice production model simulating irregular vibratory dynamics of vocal folds with a unilateral vocal polyp. Finally, we show the clinical applicability of this nonlinear detection method to analyze the electroglottographic data generated by 14 patients with vocal nodules or polyps. The VWK model method shows potential in describing the nonlinearity inherent in disordered voice productions from short and noisy time series that are common in the clinical setting.

► The VWK method effectively detects the nonlinearity of a discrete map. ► The method describes the chaotic time series of a biomechanical vocal fold model. ► Nonlinearity in laryngeal pathology is detected from short and noisy time series.