Multifractal formalism for functions part I: results valid for all functions
SIAM Journal on Mathematical Analysis
Multifractality of decomposed EEG during imaginary and real visual-motor tracking
Biological Cybernetics
Non-linear analysis of EEG signals at various sleep stages
Computer Methods and Programs in Biomedicine
Fluctuation dynamics in electroencephalogram time series
IWINAC'05 Proceedings of the First international conference on Mechanisms, Symbols, and Models Underlying Cognition: interplay between natural and artificial computation - Volume Part I
| Hi-index | 0.01 |
The task is to estimate quantitatively the changes in functional states arising in the human brain with different neural disruptions. To solve the task we analyze long-lasting recordings from patients with epilepsy and subjects with chronic psychogenic pain disorders. Using the wavelet transform of the electroencephalographic (EEG) segments and the wavelet-transform modulus maxima method we evaluate the maximal global energy of the segment and its multifractal parameters such as the width and the asymmetry of the singularity spectrum. By contrast to the segments gained for functional probes like opening eyes or hyperventilation in recordings without the epileptic discharges, the segments immediately preceding the epileptic seizure are characterized by the significant changes in the global energy and the width of the singularity spectrum. It gives promise that the applied methods can not only serve for automatically detecting the epileptic patterns but also predict modifications in the epileptic brain activity before epileptic discharges. For the patients with psychogenic pain syndromes we demonstrate the efficiency of the used parameters to evaluate objectively the improvement of the functional state connected with the pain disappearance.