Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring
Wearable sensor systems will soon become part of the available medical tools for remote and long term physiological monitoring. However, the set of variables involved in the performance of these systems are usually antagonistic, and therefore the design of usable wearable systems in real clinical ap...
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doaj-08559cd82ec7434bbf4496b5be5461a12020-11-24T22:52:38ZengHindawi LimitedJournal of Sensors1687-725X1687-72682016-01-01201610.1155/2016/24180652418065Multiobjective Design of Wearable Sensor Systems for Electrocardiogram MonitoringF. J. Martinez-Tabares0Y. J. Costa-Salas1D. Cuesta-Frau2G. Castellanos-Dominguez3Signal Processing and Recognition Group, Universidad Nacional de Colombia, Km. 7, Manizales, ColombiaUniversity of Applied Sciences, Upper Austria, 4600 Wels, AustriaTechnological Institute of Informatics (ITI), Polytechnic University of Valencia, Alcoi Campus, Plaza Ferrandiz y Carbonell 2, 03801 Alcoy, SpainSignal Processing and Recognition Group, Universidad Nacional de Colombia, Km. 7, Manizales, ColombiaWearable sensor systems will soon become part of the available medical tools for remote and long term physiological monitoring. However, the set of variables involved in the performance of these systems are usually antagonistic, and therefore the design of usable wearable systems in real clinical applications entails a number of challenges that have to be addressed first. This paper describes a method to optimise the design of these systems for the specific application of cardiac monitoring. The method proposed is based on the selection of a subset of 5 design variables, sensor contact, location, and rotation, signal correlation, and patient comfort, and 2 objective functions, functionality and wearability. These variables are optimised using linear and nonlinear models to maximise those objective functions simultaneously. The methodology described and the results achieved demonstrate that it is possible to find an optimal solution and therefore overcome most of the design barriers that prevent wearable sensor systems from being used in normal clinical practice.http://dx.doi.org/10.1155/2016/2418065 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
F. J. Martinez-Tabares Y. J. Costa-Salas D. Cuesta-Frau G. Castellanos-Dominguez |
spellingShingle |
F. J. Martinez-Tabares Y. J. Costa-Salas D. Cuesta-Frau G. Castellanos-Dominguez Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring Journal of Sensors |
author_facet |
F. J. Martinez-Tabares Y. J. Costa-Salas D. Cuesta-Frau G. Castellanos-Dominguez |
author_sort |
F. J. Martinez-Tabares |
title |
Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring |
title_short |
Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring |
title_full |
Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring |
title_fullStr |
Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring |
title_full_unstemmed |
Multiobjective Design of Wearable Sensor Systems for Electrocardiogram Monitoring |
title_sort |
multiobjective design of wearable sensor systems for electrocardiogram monitoring |
publisher |
Hindawi Limited |
series |
Journal of Sensors |
issn |
1687-725X 1687-7268 |
publishDate |
2016-01-01 |
description |
Wearable sensor systems will soon become part of the available medical tools for remote and long term physiological monitoring. However, the set of variables involved in the performance of these systems are usually antagonistic, and therefore the design of usable wearable systems in real clinical applications entails a number of challenges that have to be addressed first. This paper describes a method to optimise the design of these systems for the specific application of cardiac monitoring. The method proposed is based on the selection of a subset of 5 design variables, sensor contact, location, and rotation, signal correlation, and patient comfort, and 2 objective functions, functionality and wearability. These variables are optimised using linear and nonlinear models to maximise those objective functions simultaneously. The methodology described and the results achieved demonstrate that it is possible to find an optimal solution and therefore overcome most of the design barriers that prevent wearable sensor systems from being used in normal clinical practice. |
url |
http://dx.doi.org/10.1155/2016/2418065 |
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