Incorporating Uncertainty In Data Labeling Into Detection Of Brain Interictal Epileptiform Discharges From Eeg Using Weighted Optimization

Interictal epileptiform discharges (IEDs) can have various morphologies as well as spatial distributions and sometimes are associated with other brain activities, resulting in uncertainty in their labeling. Such an uncertainty corresponds to the probability of a waveform being an IED. Here, we incorporate this probability in an IED detection system which combines spatial component analysis (SCA) with the IED probabilities referred to as SCA-IEDP-based method. For comparison, we also propose SCA-based method in which the probability of being IED is ignored. The outcome shows that the SCA-IEDP outperforms SCA.