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EEGcorco is a computer program designed to analyze the degree of synchronization between two electroencephalographic signals EEG by mean the analysis of correlation and coherence index. The correlation and coherence values permit the quantitative determination of the similarity among EEG signals from homologous areas of the cerebral hemispheres interhemispheric, and among localized areas within one cerebral hemisphere intrahemispheric. EEG coherence is a function of frequency; thus it is commonly presented in a spectral manner coherence values in every frequency of the spectrum, in contrast, the correlation function has been employed mainly to search periodic components of bioelectrical signals, and normally appears as punctual values defined in time, hence it is not common calculate correlation spectra. EEGcorco offers an easy and novel way to calculate correlation spectra by mean the application of the Fast Fourier Transformation FFT to digitized EEG signals. Both, correlation and coherence spectra are obtained in both independent frequencies and frequencies grouped in wide bands. Moreover, the program applies parametric statistical analyses to those coherence and correlation spectra also, for each individual frequency and for the frequencies grouped in bands. The program functions on any PC-compatible computer equipped with a Pentium or superior processor and a minimum of 512 Mb of RAM memory though the higher the capacity the better. The space required on the hard disk depends on the signals to be analyzed, as the output takes the form of files in text format that occupy very little space. The program has been elaborated completely in the Delphi environment for the Windows operating system. The efficacy and versatility of EEGcorco allow it to be easily adapted to different experimental and clinical needs.

KEYWORDS

EEG; EEG Coherence; EEG Correlation

Cite this paper

Guevara, M. , Hernández-González, M. , Sanz-Martin, A. and Amezcua, C. 2011 EEGcorco: a computer program to simultaneously calculate and statistically analyze EEG coherence and correlation. Journal of Biomedical Science and Engineering, 4, 774-787. doi: 10.4236-jbise.2011.412096.





Autor: Miguel Angel Guevara, Marisela Hernández-González, Araceli Sanz-Martin, Claudia Amezcua

Fuente: http://www.scirp.org/



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