Wavelet analysis in coherence estimation of electroencephalographic signals in children for the detection of dyslexia-related abnormalitites
An approach based on the estimation of the coherence using wavelet analysis is applied to EEG and ERP signals for the detection of pathological patterns related with dyslexia. Coherence can be defined as the correlation of two signals in the frequency domain. The continuous wavelet transform was use...
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| Άλλοι συγγραφείς: | |
| Μορφή: | Thesis |
| Γλώσσα: | Greek |
| Έκδοση: |
2008
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| Διαθέσιμο Online: | http://nemertes.lis.upatras.gr/jspui/handle/10889/1155 |
| Περίληψη: | An approach based on the estimation of the coherence using wavelet analysis is applied to EEG and ERP signals for the detection of pathological patterns related with dyslexia. Coherence can be defined as the correlation of two signals in the frequency domain. The continuous wavelet transform was used for the computation of spectral characteristics since it provides highly overlapping windows which improve the reliability of the coherence estimate. This is achieved by increasing the number of segments over which the spectrum is averaged and thereby half of the amount of data is needed. Statistical analysis of the results revealed significant differences between controls and dyslexics in EEG(F3 gamma band), ERP-P50H(F3 gamma band) and attentive ERP-N100L(F3, C3 and Cz alpha band). It has also been shown that there are significant differences related with handiness and age. It is believed that signal recording from these electrodes may reflect brain areas concerning auditory and memory processing. |
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