Implementation of Compressed Sensing in Telecardiology Sensor Networks
Mobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations are frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to unavoidable power consumption limitations, the amou...
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Online Access: | http://dx.doi.org/10.1155/2010/127639 |
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doaj-789b2e3cae0840f190baa0540132ed332020-11-24T22:40:05ZengHindawi LimitedInternational Journal of Telemedicine and Applications1687-64151687-64232010-01-01201010.1155/2010/127639127639Implementation of Compressed Sensing in Telecardiology Sensor NetworksEduardo Correia Pinheiro0Octavian Adrian Postolache1Pedro Silva Girão2Instituto de Telecomunicações, Instituto Superior Técnico, Torre Norte, piso 10, Avenue Rovisco Pais, 1, 1049-001 Lisboa, PortugalInstituto de Telecomunicações, Instituto Superior Técnico, Torre Norte, piso 10, Avenue Rovisco Pais, 1, 1049-001 Lisboa, PortugalInstituto de Telecomunicações, Instituto Superior Técnico, Torre Norte, piso 10, Avenue Rovisco Pais, 1, 1049-001 Lisboa, PortugalMobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations are frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to unavoidable power consumption limitations, the amount of data acquired, processed, and transmitted needs to be diminished, which is counterproductive, regarding the quality of the information produced. Compressed sensing implementation in wireless sensor networks (WSNs) promises to bring gains not only in power savings to the devices, but also with minor impact in signal quality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm states that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates the compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy management, and the improvements accomplished by in-network processing.http://dx.doi.org/10.1155/2010/127639 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Eduardo Correia Pinheiro Octavian Adrian Postolache Pedro Silva Girão |
spellingShingle |
Eduardo Correia Pinheiro Octavian Adrian Postolache Pedro Silva Girão Implementation of Compressed Sensing in Telecardiology Sensor Networks International Journal of Telemedicine and Applications |
author_facet |
Eduardo Correia Pinheiro Octavian Adrian Postolache Pedro Silva Girão |
author_sort |
Eduardo Correia Pinheiro |
title |
Implementation of Compressed Sensing in Telecardiology Sensor Networks |
title_short |
Implementation of Compressed Sensing in Telecardiology Sensor Networks |
title_full |
Implementation of Compressed Sensing in Telecardiology Sensor Networks |
title_fullStr |
Implementation of Compressed Sensing in Telecardiology Sensor Networks |
title_full_unstemmed |
Implementation of Compressed Sensing in Telecardiology Sensor Networks |
title_sort |
implementation of compressed sensing in telecardiology sensor networks |
publisher |
Hindawi Limited |
series |
International Journal of Telemedicine and Applications |
issn |
1687-6415 1687-6423 |
publishDate |
2010-01-01 |
description |
Mobile solutions for patient cardiac monitoring are viewed with growing interest, and improvements on current implementations are frequently reported, with wireless, and in particular, wearable devices promising to achieve ubiquity. However, due to unavoidable power consumption limitations, the amount of data acquired, processed, and transmitted needs to be diminished, which is counterproductive, regarding the quality of the information produced.
Compressed sensing implementation in wireless sensor networks (WSNs) promises to bring gains not only in power savings to the devices, but also with minor impact in signal quality. Several cardiac signals have a sparse representation in some wavelet transformations. The compressed sensing paradigm states that signals can be recovered from a few projections into another basis, incoherent with the first. This paper evaluates the compressed sensing paradigm impact in a cardiac monitoring WSN, discussing the implications in data reliability, energy management, and the improvements accomplished by in-network processing. |
url |
http://dx.doi.org/10.1155/2010/127639 |
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1725705985801060352 |