Objective: Real-time EKG-based automated seizure detection is emerging as a complement or supplement to that based on cortical signals, but its value is unproven. This study assesses the clinically relevance of EKG-based seizure detection by comparing the information content in EKG and ECoG. Methods: ECoGs (6935 h; 241 clinical and 4311 sub-clinical seizures) with simultaneous EKG from 81 subjects undergoing surgical evaluation were used in these analyses. Differences, if any, between clinical and sub-clinical seizures in variables such as intensity, duration and their product severity, were investigated with a multi-variate regression model. Results: Highly statistically significant differences in severity between clinical and sub-clinical seizures were discerned with EKG and ECoG. Furthermore, EKG-based seizure severity was linearly correlated with that estimated using ECoG. Conclusions: These findings support the notion that EKG-based seizure detection is clinically relevant in certain localization-related epilepsies, providing similar information to that yielded by neuronal electrical signals. Significance: The information content equivalence between EKG and ECoG would enable automated seizure detection, quantification and therapy delivery, without resorting to cortical monitoring. The considerably higher S/N and ease of acquisition and processing of EKG compared to ECoG/EEG may foster widespread clinical applications of this novel detection approach. (C) 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.