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Título : Estimation of emptying urinary bladder in paraplegic and elderly people based on bioimpedance, hypogastric region temperature and neural network
Otros títulos : 
Autor: Rodas, Michael
Amoroso Calle, Layla Domenica
Huerta, Mónica karel
Correspondencia: Rodas, Michael, mrodasa1@est.ups.edu.ec
Palabras clave : Bioimpedance
Hypogastric Region Temperature
Neural Network
Área de conocimiento FRASCATI amplio: 3. Ciencias Médicas y de la Salud
Área de conocimiento FRASCATI detallado: 3.2.22 Urología y Nefrología
Área de conocimiento FRASCATI específico: 3.2 Medicina Clínica
Área de conocimiento UNESCO amplio: 09 - Salud y Bienestar
ÁArea de conocimiento UNESCO detallado: 0912 - Medicina
Área de conocimiento UNESCO específico: 091 - Salud
Fecha de publicación : 2018
Volumen: volumen 68, número 2
Fuente: IFMBE Proceedings
metadata.dc.identifier.doi: 10.1007/978-981-10-9038-7_172
Editor: Springer Verlag
Ciudad: 
Praga
Tipo: ARTÍCULO DE CONFERENCIA
Abstract: 
As is known, bioimpedance is a measurement method that can be used in medicine to know the volume of a person’s urinary bladder. However, this method is not entirely reliable due to the multiple factors that influence its measurement, such as the weight of the person, body fat and even the different skin type of each person. Therefore, this paper proposes a method that combines bioimpedance, hypogastric region temperature and an artificial feed-forward neural network, sufficiently capable of determining when to empty the bladder, so that this muscle is not affected by the time exceeded of urine continence, this work is aimed to people who have suffered injuries to their spine, who do not have the ability of feeling when their bladder needs to be emptied. It is also aimed to older adults who begin to have problems with their bladder control, allowing them to improve their quality of life. © Springer Nature Singapore Pte Ltd. 2019.
Resumen : 
As is known, bioimpedance is a measurement method that can be used in medicine to know the volume of a person’s urinary bladder. However, this method is not entirely reliable due to the multiple factors that influence its measurement, such as the weight of the person, body fat and even the different skin type of each person. Therefore, this paper proposes a method that combines bioimpedance, hypogastric region temperature and an artificial feed-forward neural network, sufficiently capable of determining when to empty the bladder, so that this muscle is not affected by the time exceeded of urine continence, this work is aimed to people who have suffered injuries to their spine, who do not have the ability of feeling when their bladder needs to be emptied. It is also aimed to older adults who begin to have problems with their bladder control, allowing them to improve their quality of life. © Springer Nature Singapore Pte Ltd. 2019.
URI : http://dspace.ucuenca.edu.ec/handle/123456789/33292
https://www.scopus.com/record/display.uri?eid=2-s2.0-85048233396&doi=10.1007%2f978-981-10-9038-7_172&origin=inward&txGid=a164fe49f3ec54858bbdfe2c6a8cb616
URI Fuente: https://www.springer.com/series/7403
ISBN : 978-981-10-9037-0, 978-981-10-9038-7(e)
ISSN : 1680-0737
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