EEG processing with TESPAR for depth of anesthesia detection

Poster presentation: Introduction Adequate anesthesia is crucial to the success of surgical interventions and subsequent recovery. Neuroscientists, surgeons, and engineers have sought to understand the impact of anesthet
Poster presentation: Introduction Adequate anesthesia is crucial to the success of surgical interventions and subsequent recovery. Neuroscientists, surgeons, and engineers have sought to understand the impact of anesthetics on the information processing in the brain and to properly assess the level of anesthesia in an non-invasive manner. Studies have indicated a more reliable depth of anesthesia (DOA) detection if multiple parameters are employed. Indeed, commercial DOA monitors (BIS, Narcotrend, M-Entropy and A-line ARX) use more than one feature extraction method. Here, we propose TESPAR (Time Encoded Signal Processing And Recognition) a time domain signal processing technique novel to EEG DOA assessment that could enhance existing monitoring devices. ...
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Metadaten
Author:Vasile V. Moca, Bertram Scheller, Raul C. Mureşan, Michael Daunderer, Gordon Pipa
URN:urn:nbn:de:hebis:30-70972
Document Type:Article
Language:English
Date of Publication (online):2009/09/20
Year of first Publication:2009
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2009/09/20
Note:
© 2009 Moca et al; licensee BioMed Central Ltd.
Source:BMC Neuroscience 2009, 10(Suppl 1):P68 ; doi:10.1186/1471-2202-10-S1-P68 ; from Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18–23 July 2009 ; http://www.biomedcentral.com/1471-2202/10/S1/P68
HeBIS PPN:219390592
Institutes:Medizin
Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Sondersammelgebiets-Volltexte
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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