Epileptic seizure detection using singular values and classical features of EEG signals
In this paper, an epileptic seizure event detection algorithm utilizing five features namely singular values, total average power, delta band average power, variance and mean, is proposed. Using CHB-MIT Scalp EEG Database, the calculations of the features are performed over a sliding window of one s...
| Main Authors: | Elmahdy, A.E., Yahya, N., Kamel, N.S., Shahid, A. |
|---|---|
| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.31634 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2015
|
| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961793416&doi=10.1109%2fICBAPS.2015.7292238&partnerID=40&md5=ef42740f7c30ddbfbee8db2f51195d29 http://eprints.utp.edu.my/31634/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
utp-eprints.31634 |
|---|---|
| recordtype |
eprints |
| spelling |
utp-eprints.316342022-03-26T03:24:43Z Epileptic seizure detection using singular values and classical features of EEG signals Elmahdy, A.E. Yahya, N. Kamel, N.S. Shahid, A. In this paper, an epileptic seizure event detection algorithm utilizing five features namely singular values, total average power, delta band average power, variance and mean, is proposed. Using CHB-MIT Scalp EEG Database, the calculations of the features are performed over a sliding window of one second. The algorithm was evaluated in terms of accuracy, sensitivity, specificity and failure rate. This investigation used SVM as the classification technique. The performance comparisons are made with techniques based on classical features alone, singular value alone and combination of classical features and singular values. The results show that the proposed algorithm achieves better results than using singular values alone or using classical features alone with an average accuracy of 94.82. © 2015 IEEE. Institute of Electrical and Electronics Engineers Inc. 2015 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961793416&doi=10.1109%2fICBAPS.2015.7292238&partnerID=40&md5=ef42740f7c30ddbfbee8db2f51195d29 Elmahdy, A.E. and Yahya, N. and Kamel, N.S. and Shahid, A. (2015) Epileptic seizure detection using singular values and classical features of EEG signals. In: UNSPECIFIED. http://eprints.utp.edu.my/31634/ |
| institution |
Universiti Teknologi Petronas |
| collection |
UTP Institutional Repository |
| description |
In this paper, an epileptic seizure event detection algorithm utilizing five features namely singular values, total average power, delta band average power, variance and mean, is proposed. Using CHB-MIT Scalp EEG Database, the calculations of the features are performed over a sliding window of one second. The algorithm was evaluated in terms of accuracy, sensitivity, specificity and failure rate. This investigation used SVM as the classification technique. The performance comparisons are made with techniques based on classical features alone, singular value alone and combination of classical features and singular values. The results show that the proposed algorithm achieves better results than using singular values alone or using classical features alone with an average accuracy of 94.82. © 2015 IEEE. |
| format |
Conference or Workshop Item |
| author |
Elmahdy, A.E. Yahya, N. Kamel, N.S. Shahid, A. |
| spellingShingle |
Elmahdy, A.E. Yahya, N. Kamel, N.S. Shahid, A. Epileptic seizure detection using singular values and classical features of EEG signals |
| author_sort |
Elmahdy, A.E. |
| title |
Epileptic seizure detection using singular values and classical features of EEG signals |
| title_short |
Epileptic seizure detection using singular values and classical features of EEG signals |
| title_full |
Epileptic seizure detection using singular values and classical features of EEG signals |
| title_fullStr |
Epileptic seizure detection using singular values and classical features of EEG signals |
| title_full_unstemmed |
Epileptic seizure detection using singular values and classical features of EEG signals |
| title_sort |
epileptic seizure detection using singular values and classical features of eeg signals |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2015 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961793416&doi=10.1109%2fICBAPS.2015.7292238&partnerID=40&md5=ef42740f7c30ddbfbee8db2f51195d29 http://eprints.utp.edu.my/31634/ |
| _version_ |
1741197609835429888 |
| score |
11.62408 |