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.