Vocal folds simulators have been identified as useful tool for understanding the human larynx behavior in pathophysiological conditions. The main objective of the present study is to develop a vocal folds simulator and to provide a quantitative method for monitoring synthetic replica vibration in pathophysiologic conditions, based on electroglottography (EGG). The biorobotic simulator is developed following the composition of a three-layer synthetic model with the addition of a superficial conductive layer in order to acquire an electrical signal to be compared to an EGG signal. Results showed an inverse correlation between vocal folds contact area and resistance during vibration, suggesting that the developed simulator is able to replicate the EGG signal in physiological conditions. This tool has potential for simulating multiple pathologies and clustering the derived EGG signals according to their characteristics, in order to help clinicians in the diagnosis of laryngeal diseases.

A biorobotic simulator of vocal folds for the reproduction and analysis of electroglottographic signals

Conte, Arianna;Maselli, Martina
;
Manti, Mariangela;Cianchetti, Matteo
2021-01-01

Abstract

Vocal folds simulators have been identified as useful tool for understanding the human larynx behavior in pathophysiological conditions. The main objective of the present study is to develop a vocal folds simulator and to provide a quantitative method for monitoring synthetic replica vibration in pathophysiologic conditions, based on electroglottography (EGG). The biorobotic simulator is developed following the composition of a three-layer synthetic model with the addition of a superficial conductive layer in order to acquire an electrical signal to be compared to an EGG signal. Results showed an inverse correlation between vocal folds contact area and resistance during vibration, suggesting that the developed simulator is able to replicate the EGG signal in physiological conditions. This tool has potential for simulating multiple pathologies and clustering the derived EGG signals according to their characteristics, in order to help clinicians in the diagnosis of laryngeal diseases.
2021
978-1-7281-7713-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/539616
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