Detection and analysis of epileptic seizures is of clinical and research interest. We propose a novel seizure detection and analysis scheme based on the phase-slope index (PSI) of directed influence applied to multichannel electrocorticogram data. The PSI metric identifies increases in the spatio-temporal interactions between channels that clearly distinguish seizure from interictal activity. We form a global metric of interaction between channels and compare this metric to a threshold to detect the presence of seizures. The threshold is chosen based on a moving average of recent activity to accommodate differences between patients and slow changes within each patient over time. We evaluate detection performance over a challenging population of five patients with different types of epilepsy using a total of 47 seizures in nearly 258 h of recorded data. Using a common threshold procedure, we show that our approach detects all of the seizures in four of the five patients with a false detection rate less than two per hour. A variation on the global metric is proposed to identify which channels are strong drivers of activity in each patient. These metrics are computationally efficient and suitable for real-time application. © 2006 IEEE.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Manuscript received May 16, 2011; revised October 31, 2011; accepted December 19, 2011. Date of publication January 18, 2012; date of current version March 21, 2012. This work was supported in part by the National Institutes of Health under award R21EB009749 and the Dr. Ralph and Marian Falk Medical Research Trust. Asterisk indicates corresponding author.
ASJC Scopus subject areas
- Biomedical Engineering