Parametric method for the analysis of temporal and spatial variability in the interictal EEG signal

G. Tognola, P. Ravazzani, T. Locatelli, F. Minicucci, F. Grandori, G. Comi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The analysis of variability in the EEG signal is a relatively new field of investigation. This is mainly due to the objective difficulty to develop quantitative methods of analysis. Autoregressive modeling of the EEG signal is proposed to quantify its variability. Model coefficients were computed from adjacent epochs and their temporal behavior was analyzed: background activity produced only very slow temporal changes, while a variability in the EEG provoked sharp changes in the AR sequences. To quantify the variability with a numerical value (Difference Measure, DM), the AR sequences were processed by means of a segmentation algorithm. DMs were derived for all EEG leads and analyzed under visual inspection. Preliminary results show that this approach could be of some help in the study of temporal and spatial characteristics of interictal epileptiform discharges.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages1234-1235
Number of pages2
Volume16
Editionpt 2
Publication statusPublished - 1994
EventProceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2) - Baltimore, MD, USA
Duration: Nov 3 1994Nov 6 1994

Other

OtherProceedings of the 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 1 (of 2)
CityBaltimore, MD, USA
Period11/3/9411/6/94

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ASJC Scopus subject areas

  • Bioengineering

Cite this

Tognola, G., Ravazzani, P., Locatelli, T., Minicucci, F., Grandori, F., & Comi, G. (1994). Parametric method for the analysis of temporal and spatial variability in the interictal EEG signal. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pt 2 ed., Vol. 16, pp. 1234-1235). IEEE.