Subglottal Impedance-Based Model Parameter Estimation via System Identification
Year: 2024
Type: article
Abstract: Accurate mathematical modeling of different systems of the human body stands as a key issue in medical and bioengineering applications. This paper specifically considers the continuous-time parameter estimation of the impedance-based mathematical model — a mechano-acoustic representation of the subglottal system. This approach allows the customization of the model for each patient. A key advantage of having a patient-dependent model of the subglottal system is to facilitate the ambulatory non-invasive monitoring of the glottal airflow and the assessment of vocal functions, using an accelerometer on the neck skin surface. For this model of the subglottal system, the glottal airflow is the excitation signal, while the acceleration on the neck skin is the system response. In this study, continuous-time parameter estimation of the impedance-based model for the subglottal system is applied, using both frequency response and sampled data through system identification techniques.
Source: IFAC-PapersOnLine
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Awards: CONTINUOUS-TIME NONLINEAR SYSTEM IDENTIFICATION USING DEEP LEARNING, G371350066, G3980701974, GLOTTAL AERODYNAMICS ESTIMATED FROM INVERSE FILTERED NECK-SURFACE VIBRATION IN SUBJECTS WITH PHONOTRAUMATIC AND NONPHONOTRAUMATIC VOCAL HYPERFUNCTION, G536736570, G5600568622, ADVANCED CENTER FOR ELECTRICAL AND ELECTRONIC ENGINEERING, PARAMETER ESTIMATION OF THE SUBGLOTTAL MODEL USING SYSTEM IDENTIFICATION, G6641207296, G668553494, G7137581656, G8066241005, G9000003783
OpenAlex ID: W4402641427