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Báo cáo khoa hoc:" A decision support framework for the discrimination of children with controlled epilepsy based on EEG analysis"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: A decision support framework for the discrimination of children with controlled epilepsy based on EEG analysis | Sakkalis et al. Journal of NeuroEngineering and Rehabilitation 2010 7 24 http www.jneuroengrehab.eom content 7 1 24 J NER JOURNAL OF NEUROENGINEERING AND REHABILITATION RESEARCH Open Access A decision support framework for the discrimination of children with controlled epilepsy based on EEG analysis Vangelis Sakkalis 1 Tracey Cassar2 Michalis Zervakis3 Ciprian D Giurcaneanu4 Cristin Bigan5 Sifis Micheloyannis6 Kenneth P Camilleri2 Simon G Fabri2 Eleni Karakonstantaki6 and Kostas Michalopoulos3 Abstract Background In this work we consider hidden signs biomarkers in ongoing EEG activity expressing epileptic tendency for otherwise normal brain operation. More specifically this study considers children with controlled epilepsy where only a few seizures without complications were noted before starting medication and who showed no clinical or electrophysiological signs of brain dysfunction. We compare EEG recordings from controlled epileptic children with age-matched control children under two different operations an eyes closed rest condition and a mathematical task. The aim of this study is to develop reliable techniques for the extraction of biomarkers from EEG that indicate the presence of minor neurophysiological signs in cases where no clinical or significant EEG abnormalities are observed. Methods We compare two different approaches for localizing activity differences and retrieving relevant information for classifying the two groups. The first approach focuses on power spectrum analysis whereas the second approach analyzes the functional coupling of cortical assemblies using linear synchronization techniques. Results Differences could be detected during the control rest task but not on the more demanding mathematical task. The spectral markers provide better diagnostic ability than their synchronization counterparts even though a combination or fusion of both is needed for efficient classification of subjects. Conclusions Based on these differences the study .