Online seizure detection in adults with temporal lobe epilepsy using single-lead ECG

In this paper, a patient-independent algorithm for online epileptic seizure detection using only single-lead ECG is proposed. It is tested on 300h of data from adults with temporal lobe epilepsy. The features are extracted from a period of linear increase of the heart rate, which typically occurs in this kind of patients. These features are classified by two different classifiers: linear support vector machine (LSVM) and linear discriminant analysis (LDA). The best performance is found for LDA with a sensitivity of 80.0%, a PPV of 40.5% and an average detection delay of 31.5s, which are satisfactory results for online usage in monitoring or warning systems.