Spirometry takes care to find and to predict respiratory system pathologies through instrumentation that mainly carries out measurements on the volume and the air flow expired from lungs. A complete spirometric instrumentation composed of three parts has been developed. The first part, ldquohardwarerdquo, gains a sampled signal from a sensor of the flow-time curve and sends it to the computer. The second part, ldquosoftwarerdquo, processes received data calculating the volume-time curve, the flow-volume curve and other main spirometric parameters, displaying the result of prediction. The last part, ldquoa genetic algorithmrdquo, trains itself on the base of a series of computing with real data, to produce spirometric parameters of a most likely pathologic curve and, to predict pathology type with less possible tests

Breath Flow Sensing via Spirometric Instrumentation: Pathology Prediction Using a Genetic Algorithm / Lay-Ekuakille, A.; Vendramin, G.; Trotta, A.. - STAMPA. - (2008), pp. 4757120.313-4757120.317. (Intervento presentato al convegno The 3rd IEEE-ICST International Conference on Sensing Technology tenutosi a Tainan, Taiwan nel November 30 - December 3, 2008) [10.1109/ICSENST.2008.4757120].

Breath Flow Sensing via Spirometric Instrumentation: Pathology Prediction Using a Genetic Algorithm

Trotta, A.
2008-01-01

Abstract

Spirometry takes care to find and to predict respiratory system pathologies through instrumentation that mainly carries out measurements on the volume and the air flow expired from lungs. A complete spirometric instrumentation composed of three parts has been developed. The first part, ldquohardwarerdquo, gains a sampled signal from a sensor of the flow-time curve and sends it to the computer. The second part, ldquosoftwarerdquo, processes received data calculating the volume-time curve, the flow-volume curve and other main spirometric parameters, displaying the result of prediction. The last part, ldquoa genetic algorithmrdquo, trains itself on the base of a series of computing with real data, to produce spirometric parameters of a most likely pathologic curve and, to predict pathology type with less possible tests
2008
The 3rd IEEE-ICST International Conference on Sensing Technology
978-1-4244-2176-3
Breath Flow Sensing via Spirometric Instrumentation: Pathology Prediction Using a Genetic Algorithm / Lay-Ekuakille, A.; Vendramin, G.; Trotta, A.. - STAMPA. - (2008), pp. 4757120.313-4757120.317. (Intervento presentato al convegno The 3rd IEEE-ICST International Conference on Sensing Technology tenutosi a Tainan, Taiwan nel November 30 - December 3, 2008) [10.1109/ICSENST.2008.4757120].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/22513
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