AN ONLINE SPIKE DETECTION AND MONITORING FRAMEWORK IN IEEG RECORDED USING BRAIN INTERCHANGE DEVICE

In this study, we developed and validated an online analysis framework in MATLAB Simulink for recording and analysis of intracranial electroencephalography (iEEG). This framework aims to detect interictal spikes in patients with epilepsy as the data is being recorded. An online spike detection was performed over 10-minute interictal iEEG data recorded with Brain Interchange CorTec in three human subjects. A pool of detected spikes is then broadcasted using User Datagram Protocol (UDP) to an external graphical user interface for further post-processing and visualization. The real-time spike detector demonstrated a 99% similarity index with the previously published offline detector, identifying interictal spikes. Furthermore, our findings indicated that channels with highest spike rates, captured with Brain Interchange CorTec, were in the epileptogenic focus. By enabling the detection of interictal spikes in an online fashion, this work provides early feedback on the probable seizure onset zone (SOZ) and suggests a promising direction for enhancing SOZ localization accuracy to clinicians, which is crucial for the surgical treatment of epilepsy.