Complex Network Analysis Of Resting State Electroencephalography in Stroke

Stroke, with high morbidity and mortality, causes great damage to the brain and is common in the elderly population. Other than magnetic resonance imaging (MRI) or computed tomography (CT), less reliable objective method is currently available for assessing the patient's condition clinically. In this work, we develop an electroencephalography(EEG) analysis to find features that show a significant difference between stroke patients and healthy people. The phase-locked value and complex network analysis were chosen in this study. In presenting the global and local parameters, we found a source of features that may show details of network changes in patients.