Implementación de un sistema con inteligencia computacional para identificar dificultad respiratoria a partir del procesamiento digital de señales de voz

The developed system incorporates computational intelligence, this allows to identify people with respiratory distress (caused by influenza) in an automatic and non-invasive way, from the digital processing of voice signals, integrating the calculation of acoustic, spectral, temporal and statistical parameters, which implemented in a client-server architecture, they allow the respective analysis, obtained as a result of the recording of two sustained vowel sounds (vowel "a" and "o"), through the microphone of a mobile device of a Spanish-speaking population group aged between 18 and 49 years old. The results obtained determine that for the detection of respiratory distress, the vowel "a" is more efficient in women with a hit rate of 97.62% and the vowel "o" in men; reaching a hit rate of 96.77%. This system is expected to contribute to new support tools with potential for application in health, to promote biosafety protocols, especially in this context of a Covid-19 pandemic; illness that causes respiratory distress, like the flu.

• Autores: Fernández Velasco, Sara Isabel; Ramos Casanova, Karen Andrea
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2021
• Institución: Universidad Antonio Nariño
• Repositorio: Repositorio UAN
• Idioma: spa
• OAI Identifier: oai:repositorio.uan.edu.co:123456789/5974
• Acceso en línea: http://repositorio.uan.edu.co/handle/123456789/5974
• Palabra clave: Sistema computacional; inteligencia computacional; parámetros acústicos; dificultad respiratoria; voz; Computational system; voice; respiratory distress; acoustic parameters; computational intelligence.
• Rights: openAccess
• License: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)