A unified treatment of the reference estimation problem in depth EEG recordings.
The starting point of this paper is the analysis of the reference problem in intra-cerebral electroencephalographic (iEEG) recordings. It is well accepted that both surface and depth EEG signals are always recorded with respect to some unknown time-varying signal called reference. This article discu...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 50; no. 10; pp. 1003 - 1016 |
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| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Oct2012
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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=104067281&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104067281 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Oct2012 vid: 50 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104067281 NLM22983680 2011711428 10.1007/s11517-012-0946-0 NLM22983680 104067281 ppf: 1003 ppct: 13 formats: fmt: @attributes: type: P tig: atl: A unified treatment of the reference estimation problem in depth EEG recordings. aug: au: Madhu N Ranta R Maillard L Koessler L Madhu, Nilesh Ranta, Radu Maillard, Louis Koessler, Laurent affil: Division of Experimental Otorhinolaryngology, Department of Neurosciences, Katholieke Universiteit, Leuven, Belgium sug: subj: Electroencephalography Methods Signal Processing, Computer Assisted Algorithms Artifacts Electrodes, Implanted ab: The starting point of this paper is the analysis of the reference problem in intra-cerebral electroencephalographic (iEEG) recordings. It is well accepted that both surface and depth EEG signals are always recorded with respect to some unknown time-varying signal called reference. This article discusses different methods for determining and reducing the influence of the reference signal for the iEEG signals. In particular, we derive optimal approaches for the estimation of the reference signal in iEEG recording setups and demonstrate their relation to the well-known minimum power/variance distortionless response approaches derived for general array and antenna signal processing applications. We show that the proposed approaches achieve optimal performance in terms of estimation error and that they outperform other reference identification methods proposed in the literature. The developed algorithms are illustrated on simulated examples and on real iEEG signals. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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