Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/41709
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Campo DC | Valor | Idioma |
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dc.contributor.author | Portela, Filipe | por |
dc.contributor.author | Oliveira, Sérgio Manuel Costa | por |
dc.contributor.author | Santos, Manuel | por |
dc.contributor.author | Machado, José Manuel | por |
dc.contributor.author | Abelha, António | por |
dc.date.accessioned | 2016-05-20T13:58:24Z | - |
dc.date.issued | 2015 | - |
dc.identifier.isbn | 978-3-319-26507-0 | - |
dc.identifier.issn | 0302-9743 | por |
dc.identifier.uri | https://hdl.handle.net/1822/41709 | - |
dc.description.abstract | Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance. | por |
dc.language.iso | eng | por |
dc.publisher | Springer | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876/147280/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/5876-PPCDTI/126314/PT | por |
dc.rights | openAccess | - |
dc.subject | Ambient intelligence | por |
dc.subject | HealthCare | por |
dc.subject | Data streaming | por |
dc.subject | Critic events | por |
dc.subject | Intelligent systems | por |
dc.subject | Real-Time | por |
dc.subject | Tracking system | por |
dc.subject | INTCare | por |
dc.subject | Intensive care | por |
dc.title | A Real-Time intelligent system for tracking patient condition | por |
dc.type | conferencePaper | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | http://link.springer.com/chapter/10.1007%2F978-3-319-26508-7_9 | por |
sdum.publicationstatus | info:eu-repo/semantics/publishedVersion | por |
oaire.citationStartPage | 91 | por |
oaire.citationEndPage | 97 | por |
oaire.citationTitle | Ambient Intelligence for Health | por |
oaire.citationVolume | 9456 | por |
dc.identifier.doi | 10.1007/978-3-319-26508-7_9 | por |
dc.subject.wos | Science & Technology | por |
sdum.journal | Lecture Notes in Computer Science | por |
sdum.conferencePublication | AMBIENT INTELLIGENCE FOR HEALTH, AMIHEALTH 2015 | por |
sdum.bookTitle | Ambient Intelligence for Health | por |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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2015 - IWAAL - TrackSystem vfr1.pdf | 369,67 kB | Adobe PDF | Ver/Abrir |