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

Yu Zhang, Alicia J. Sprecher, ZongXi Zhao and Jack J. Jiang

Chaos, Solitons & Fractals, 2011, vol. 44, issue 9, 751-758

Abstract: 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.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:44:y:2011:i:9:p:751-758

DOI: 10.1016/j.chaos.2011.06.011

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