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...
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| Autores principales: | , |
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| Otros Autores: | |
| Formato: | Trabajo de grado (Pregrado y/o Especialización) |
| Lenguaje: | spa |
| Publicado: |
Universidad Antonio Nariño
2022
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| Materias: | |
| Acceso en línea: | http://repositorio.uan.edu.co/handle/123456789/5974 |
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| Sumario: | 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. |
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