English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Adaptive frequency decomposition of EEG with subsequent expert system analysis

MPS-Authors
/persons/resource/persons19711

Herrmann,  Christoph S.
MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

/persons/resource/persons19532

Arnold,  Thomas
MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

External Ressource
No external resources are shared
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Herrmann, C. S., Arnold, T., Visbeck, A., Hundemer, H. P., & Hopf, H. C. (2001). Adaptive frequency decomposition of EEG with subsequent expert system analysis. Computers in Biology and Medicine (Elmsford, NY), 31(6), 407-427. doi:10.1016/S0010-4825(01)00017-8.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-9AEC-C
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.