Entropy analysis on EEG signal in a case study of focal myoclonus.
Electrophysiological studies provide useful information for diagnosis and classification of myoclonus, and for the investigation of its generative mechanisms, due to association of myoclonus with abnormally increased excitability of cortical structures. In this work we analyzed the polygraphic data of a 7-year old girl affected by continuous partial epilepsy with focal myoclonus both related and not related with epileptiform discharges on EEG. We applied Sample Entropy (SampEn) and Lempel-Ziv complexity (LZ) methods to investigate the regularity and complexity content of EEG recordings and to find possible analogies in the behaviour of non-parametric complexity measures in epilepsy and in myoclonus. Our results show that these algorithms succeeded in finding a significant difference between the hypothesized focus on C3 electrode and the contralateral electrode C4, for EEG correlated myoclonus. A significant difference between the two contralateral electrodes (C3-C4) was also found for non EEG correlated myoclonus, but only by means of SampEn. This preliminary study confirmed the ability of entropic methods in discriminating myoclonic events. Indeed, near the myoclonic focus location both SampEn and LZ methods showed below average values.
Molteni
Erika
E
Politecnico di Milano, Italy. erika.molteni@polimi.it
Perego
Paolo
P
Zanotta
Nicoletta
N
Reni
Gianluigi
G
D000465:Algorithms; D002648:Child; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D019277:Entropy; D004831:Epilepsies, Myoclonic / Q000175:diagnosis / Q000503:physiopathology*; D005260:Female; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted