JOURNAL ARTICLE

Evaluation of time and frequency domain features for seizure detection from combined EEG and ECG signals

Abstract

In this paper, a large scale evaluation of time-domain and frequency domain features of electroencephalographic and electrocardiographic signals for seizure detection was performed. For the classification we relied on the support vector machines algorithm. The seizure detection architecture was evaluated on three subjects and the achieved detection accuracy was more than 90% for two of them and slightly lower than 90% for the third subject.

Keywords:
Electroencephalography Time domain Frequency domain Time–frequency analysis Computer science Pattern recognition (psychology) Support vector machine Artificial intelligence Speech recognition Epileptic seizure Feature extraction Epilepsy Psychology Computer vision Neuroscience

Metrics

12
Cited By
0.96
FWCI (Field Weighted Citation Impact)
18
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience
Blind Source Separation Techniques
Physical Sciences →  Computer Science →  Signal Processing
ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
© 2026 ScienceGate Book Chapters — All rights reserved.