We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Online Automated Seizure Detection in Temporal Lobe Epilepsy Patients Using Single-lead ECG.
- Authors
De Cooman, Thomas; Varon, Carolina; Hunyadi, Borbála; Van Paesschen, Wim; Lagae, Lieven; Van Huffel, Sabine
- Abstract
Automated seizure detection in a home environment has been of increased interest the last couple of decades. The electrocardiogram is one of the signals that is suited for this application. In this paper, a new method is described that classifies different heart rate characteristics in order to detect seizures from temporal lobe epilepsy patients. The used support vector machine classifier is trained on data from other patients, so that the algorithm can be used directly from the start of each new recording. The algorithm was tested on a dataset of more than 918h of data coming from 17 patients containing 127 complex partial and generalized partial seizures. The algorithm was able to detect 81.89% of the seizures, with on average 1.97 false alarms per hour. These results show a strong drop in the number of false alarms of more than 50% compared to other heart rate-based patient-independent algorithms from the literature, at the expense of a slightly higher detection delay of 17.8s on average.
- Subjects
TEMPORAL lobe epilepsy; SPASMS; ELECTROCARDIOGRAPHY; SUPPORT vector machines; PATIENT monitoring; PATIENTS
- Publication
International Journal of Neural Systems, 2017, Vol 27, Issue 7, p-1
- ISSN
0129-0657
- Publication type
Article
- DOI
10.1142/S0129065717500228