1. Signal processing in prolonged EEG recordings during intensive care
- Author
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S. White, Carsten E. Thomsen, K. Jensen, P.F. Prior, M. Van Gils, J. Gade, Lotfi Senhadji, R.M. Longford, Annelise Rosenfalck, I.R. Ghosh, VTT Information technology, Technical Research Centre of Finland, Departement of medical informatics and image analysis, Aalborg University [Denmark] (AAU), Departement of clinical neurophysiology, St Bartolomew's Hospital, Judex Datasystemer A/S, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Departement of oral function and physiology, University of Copenhagen = Københavns Universitet (UCPH), Anaesthetics laboratory, Departement of anaesthesiology, Hjorring hospital, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), University of Copenhagen = Københavns Universitet (KU), and Senhadji, Lotfi
- Subjects
Time Factors ,Speech recognition ,MESH: Monitoring, Physiologic ,long-term trend information ,02 engineering and technology ,prolonged EEG recordings ,Electroencephalography ,MESH: Signal Processing, Computer-Assisted ,0302 clinical medicine ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Computer equipment ,MESH: Data Collection ,medical signal processing ,IMPROVE project ,intensive care ,Signal processing ,Fourier Analysis ,medicine.diagnostic_test ,Data Collection ,Signal Processing, Computer-Assisted ,General Medicine ,Clinical Practice ,Data Display ,Encephalitis ,[SDV.IB]Life Sciences [q-bio]/Bioengineering ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Sleep Stages ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ,electroencephalography ,Adult ,Critical Care ,[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing ,Process (engineering) ,0206 medical engineering ,Biomedical Engineering ,Context (language use) ,long-term recordings ,03 medical and health sciences ,MESH: Thiopental ,Intensive care ,MESH: Electroencephalography ,MESH: European Union ,medicine ,Humans ,[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,European Union ,MESH: Intensive Care ,Thiopental ,Set (psychology) ,[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing ,Monitoring, Physiologic ,[SDV.IB] Life Sciences [q-bio]/Bioengineering ,MESH: Humans ,data recording ,IMPROVE data library ,business.industry ,patient care ,MESH: Time Factors ,MESH: Adult ,MESH: Sleep Stages ,short-term discrete events ,020601 biomedical engineering ,ICU ,MESH: Encephalitis ,relevant information extraction ,business ,MESH: Data Display ,MESH: Fourier Analysis ,030217 neurology & neurosurgery - Abstract
International audience; Methods for analyzing and displaying EEG signals are discussed. The increasing availability and affordability of powerful computer equipment makes possible the use of ever more sophisticated signal processing techniques, which extract relevant (but not readily discernible) information from long-term EEG recordings and can easily identify important features in the EEG. Whether these techniques are actually taken up in clinical practice is heavily dependent on how well they match clinical requirements. This article concentrates on requirements set in the context of long-term recordings in the ICU that demand the ability to process short-term discrete events as well as long-term trend information. A huge range of potentially useful signal processing techniques exists. This article illustrates the value of some of these techniques for ICU signals using the EEG recordings collected during the IMPROVE project
- Published
- 1997