Data Mining to Help Aphasic Quadriplegic and Coma Patients

Sanjana Sahayaraj, Shomona Gracia Jacob

Abstract: One of the major challenges in medical history has been differentiating between a brain dead person and a person in coma. Tests like apnoea can prove dangerous sometimes. The motive here is to apply data mining techniques to brain data that are obtained from EEG to differentiate between brain dead and coma patients. Here we also focus on another important application in the medical field, which is the ability to recognise the slightest response of a quadriplegic patient with aphasia to their surroundings. This is possible from EEG data. Data mining is done using new data set and present repository to obtain greater degree of accuracy.

Keywords: EEG, Aphasia, Quadriplegia, Coma, Brain waves, WEKA data mining tools