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

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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