Practical numerical algorithms for chaotic systems
Practical numerical algorithms for chaotic systems
Understanding nonlinear dynamics
Understanding nonlinear dynamics
Digital Image Processing
Nonlinear Time Series Analysis
Nonlinear Time Series Analysis
Algorithm Collections for Digital Signal Processing Applications Using Matlab
Algorithm Collections for Digital Signal Processing Applications Using Matlab
Glottal Source biometrical signature for voice pathology detection
Speech Communication
Time-frequency localization operators: a geometric phase space approach
IEEE Transactions on Information Theory
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Primary voice production occurs in the larynx through vibrational movements carried out by vocal folds. However, many problems can affect this complex system resulting in voice disorders. In this context, time-frequency-shape analysis based on embedding phase space plots and nonlinear dynamics methods have been used to evaluate the vocal fold dynamics during phonation. For this purpose, the present work used high-speed video to record the vocal fold movements of three subjects and extract the glottal area time series using an image segmentation algorithm. This signal is used for an optimization method which combines genetic algorithms and a quasi-Newton method to optimize the parameters of a biomechanical model of vocal folds based on lumped elements (masses, springs and dampers). After optimization, this model is capable of simulating the dynamics of recorded vocal folds and their glottal pulse. Bifurcation diagrams and phase space analysis were used to evaluate the behavior of this deterministic system in different circumstances. The results showed that this methodology can be used to extract some physiological parameters of vocal folds and reproduce some complex behaviors of these structures contributing to the scientific and clinical evaluation of voice production.