Adaptive frequency decomposition of EEG with subsequent expert system analysis
We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time–frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-...
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| Published in: | Computers in biology and medicine Vol. 31; no. 6; pp. 407 - 427 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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Oxford
Elsevier Ltd
01-11-2001
New York, NY Elsevier Science |
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| Abstract | We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time–frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG. |
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| AbstractList | We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG. We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG. copyright 2001 Elsevier Science Ltd. All rights reserved. |
| Author | Hopf, H.C Arnold, T Hundemer, H.-P Herrmann, C.S Visbeck, A |
| Author_xml | – sequence: 1 givenname: C.S surname: Herrmann fullname: Herrmann, C.S email: herrmann@cns.mpg.de organization: Max Planck Institute of Cognitive Neuroscience, PO Box 500 355, D-04303 Leipzig, Germany – sequence: 2 givenname: T surname: Arnold fullname: Arnold, T organization: Max Planck Institute of Cognitive Neuroscience, PO Box 500 355, D-04303 Leipzig, Germany – sequence: 3 givenname: A surname: Visbeck fullname: Visbeck, A organization: Department of Neurology, University of Mainz, Langenbeckstr. 1, D-55131 Mainz, Germany – sequence: 4 givenname: H.-P surname: Hundemer fullname: Hundemer, H.-P organization: Lilly Germany, Saalburgstr. 153, D-61350 Bad Homburg, Germany – sequence: 5 givenname: H.C surname: Hopf fullname: Hopf, H.C organization: Department of Neurology, University of Mainz, Langenbeckstr. 1, D-55131 Mainz, Germany |
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| Keywords | Fuzzy logic EEG Expert system Spectral analysis Human Evaluation Alpha rhythm Time frequency domain method Artefact Decomposition Electroencephalography Algorithm Automatic processing Electrodiagnosis Biomedical data processing Sensitivity Frequency Signal analysis Biomedical engineering |
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| SubjectTerms | Adolescent Adult Aged Aged, 80 and over Alpha Rhythm Biological and medical sciences Biometry Brain Diseases - diagnosis Brain Diseases - physiopathology Computerized, statistical medical data processing and models in biomedicine Delta Rhythm Diagnosis, Computer-Assisted EEG Electrodiagnosis. Electric activity recording Electroencephalography - statistics & numerical data Expert system Expert Systems Frequency domain analysis Fuzzy Logic General aspects. Methods Humans Investigative techniques, diagnostic techniques (general aspects) Medical sciences Middle Aged Nervous system Neurology Pathology Spectral analysis Spectrum analysis Theta Rhythm Time domain analysis |
| Title | Adaptive frequency decomposition of EEG with subsequent expert system analysis |
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