Human Identification Using Compressed ECG Signals.
As a result of the increased demand for improved life styles and the increment of senior citizens over the age of 65, new home care services are demanded. Simultaneously, the medical sector is increasingly becoming the new target of cybercriminals due the potential value of users' medical informatio...
| Publicado en: | Journal of Medical Systems Vol. 39; no. 11; pp. 1 - 11 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Nov2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925209&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925209 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Nov2015 vid: 39 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925209 115925209 115925209 10.1007/s10916-015-0323-2 115925209 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Human Identification Using Compressed ECG Signals. aug: au: Camara, Carmen Peris-Lopez, Pedro Tapiador, Juan affil: COSEC Lab (Computer Science Department), Carlos III University of Madrid, Avda de la Universidad 30, 28911 Leganes Spain sug: subj: Biometrics Patient Identification Electrocardiography Human Signal Processing, Computer Assisted Data Security Funding Source ab: As a result of the increased demand for improved life styles and the increment of senior citizens over the age of 65, new home care services are demanded. Simultaneously, the medical sector is increasingly becoming the new target of cybercriminals due the potential value of users' medical information. The use of biometrics seems an effective tool as a deterrent for many of such attacks. In this paper, we propose the use of electrocardiograms (ECGs) for the identification of individuals. For instance, for a telecare service, a user could be authenticated using the information extracted from her ECG signal. The majority of ECG-based biometrics systems extract information (fiducial features) from the characteristics points of an ECG wave. In this article, we propose the use of non-fiducial features via the Hadamard Transform (HT). We show how the use of highly compressed signals (only 24 coefficients of HT) is enough to unequivocally identify individuals with a high performance (classification accuracy of 0.97 and with identification system errors in the order of 10). pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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