Estimation of emptying urinary bladder in paraplegic and elderly people based on bioimpedance, hypogastric region temperature and neural network

Michael Rodas, Layla Amoroso, Mónica Huerta

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

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.

Original languageEnglish
Pages (from-to)931-935
Number of pages5
JournalIFMBE Proceedings
Volume68
Issue number2
DOIs
StatePublished - 1 Jan 2018
EventWorld Congress on Medical Physics and Biomedical Engineering, WC 2018 - Prague, Czech Republic
Duration: 3 Jun 20188 Jun 2018

Bibliographical note

Funding Information:
Acknowledgements We gratefully thank to the support of UAM, Universidad del Adulto Mayor of the city Cuenca and to all the patients who contributed to this study. An especial acknowledgment to Bernardo Vazquez, who was the main inspiration to develop this research. The authors gratefully acknowledge the support of the NEURO-SISMO project, Universidad Politécnica Salesiana from Ecuador.

Funding Information:
We gratefully thank to the support of UAM, Universidad del Adulto Mayor of the city Cuenca and to all the patients who contributed to this study. An especial acknowledgment to Bernardo Vazquez, who was the main inspiration to develop this research. The authors gratefully acknowledge the support of the NEURO-SISMO project, Universidad Politécnica Salesiana from Ecuador.

Publisher Copyright:
© Springer Nature Singapore Pte Ltd. 2019.

Keywords

  • Bioimpedance
  • Hypogastric region temperature
  • Neural network

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