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Sonotubometry, a useful tool for the evaluation of the Eustachian tube ventilatory function

From the three Eustachian tube (ET) functions: middle ear protection, secretion clearance and middle ear ventilation, the ventilatory function is unanimously considered the most important one, because proper hearing is established only when tympanic membrane compliance is normal. This requires equil...

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Detalles Bibliográficos
Autores principales: Borangiu, A, Popescu, CR, Purcarea, VL
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Carol Davila University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4316148/
https://www.ncbi.nlm.nih.gov/pubmed/25713631
Descripción
Sumario:From the three Eustachian tube (ET) functions: middle ear protection, secretion clearance and middle ear ventilation, the ventilatory function is unanimously considered the most important one, because proper hearing is established only when tympanic membrane compliance is normal. This requires equilibrium between the middle ear and ambient gas pressure, which makes the normal functioning of active ET opening of critical importance. There are several methods and tests that can assess such a complex and variable mechanism. Sonotubometry is one such method; despite the fact that it has been continuously improved in the last 20 years, it is not yet systematically used to evaluate the ET ventilatory function, because its measurement pattern, context mapping (patient, clinic data, medication, treatment), validation, reproducibility and value for clinic practice, have not yet been fully consolidated and integrated in a knowledge-based, service-oriented system, that can provide decision support or even diagnostic. The paper reviews the role of tubal sonometry as a non-invasive, physiologic and easy to use method in assessing the ventilatory function and investigates the validity and reproducibility of a measuring pattern and test in a group of children. The paper describes the test pattern used, and the computer-based platform based on: (1) Digital Signal Processing (DSP) for sound acquisition and low-level processing; (2) Artificial Intelligence techniques to extract significant sound features from sonotubograms and learn a manifold context database. Results are reported from test series carried out in healthy children; a similar study between tests is included in the final Discussions section.