Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring

In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedicated signal-processing packages. Integrated sensors...

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Detalles Bibliográficos
Autores principales: Adnane, Mourad, Jiang, Zhongwei, Choi, Samjin, Jang, Hoyoung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2009
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3286826/
https://www.ncbi.nlm.nih.gov/pubmed/22399978
http://dx.doi.org/10.3390/s90906897
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author Adnane, Mourad
Jiang, Zhongwei
Choi, Samjin
Jang, Hoyoung
author_facet Adnane, Mourad
Jiang, Zhongwei
Choi, Samjin
Jang, Hoyoung
author_sort Adnane, Mourad
collection PubMed
description In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedicated signal-processing packages. Integrated sensors are a PVDF film and conductive fabric sheets. The signal processing package includes dedicated respiratory cycle (RC) and QRS complex detection algorithms and a new method using the respiratory cycle variability (RCV) for detecting apnea/hypopnea periods in physiological data. Results show that our method is suitable for online analysis of long time series data.
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spelling pubmed-32868262012-03-07 Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring Adnane, Mourad Jiang, Zhongwei Choi, Samjin Jang, Hoyoung Sensors (Basel) Article In this paper, a new method for the detection of apnea/hypopnea periods in physiological data is presented. The method is based on the intelligent combination of an integrated sensor system for long-time cardiorespiratory signal monitoring and dedicated signal-processing packages. Integrated sensors are a PVDF film and conductive fabric sheets. The signal processing package includes dedicated respiratory cycle (RC) and QRS complex detection algorithms and a new method using the respiratory cycle variability (RCV) for detecting apnea/hypopnea periods in physiological data. Results show that our method is suitable for online analysis of long time series data. Molecular Diversity Preservation International (MDPI) 2009-09-01 /pmc/articles/PMC3286826/ /pubmed/22399978 http://dx.doi.org/10.3390/s90906897 Text en © 2009 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Adnane, Mourad
Jiang, Zhongwei
Choi, Samjin
Jang, Hoyoung
Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title_full Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title_fullStr Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title_full_unstemmed Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title_short Detecting Specific Health-Related Events Using an Integrated Sensor System for Vital Sign Monitoring
title_sort detecting specific health-related events using an integrated sensor system for vital sign monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3286826/
https://www.ncbi.nlm.nih.gov/pubmed/22399978
http://dx.doi.org/10.3390/s90906897
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AT janghoyoung detectingspecifichealthrelatedeventsusinganintegratedsensorsystemforvitalsignmonitoring

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