ANN classification of ischemic stroke severity using EEG sub band relative power ration

This paper presents an intelligent system for the classification of ischemic stroke severity. The application of Artificial Neural Network (ANN) is proposed in this study to classify ischemic stroke severity using EEG sub bands Relative Power Ratio (RPR). There were 100 subjects from National Stroke Association of Malaysia NASAM, Petaling Jaya, Selangor, Malaysia divided into Early Group (EG), Intermediate Group (IG) and Advance Group (AG) with 33, 36 and 31 subjects for each group. The characteristic of the ischemic stroke brainwaves were determined due to the group rehabilitation progression. The result obtained showed the capability of ANN in analyzing the ischemic stroke severity hence beneficial for the further application such as grouping the ischemic stroke severity cases correctly classify were 85%. This system will be capable of applying the most appropriate classification method to each ischemic stroke level, which widely extends the research in the field of automatic classification.