| Title |
EEGSingle-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| Authors |
ROMAINE, JAMES BRIAN, PEREIRA MARTÍN, MARIO, SALVADOR ORTIZ, JOSÉ RAMÓN, MANZANO CRESPO, JOSÉ MARÍA |
| External publication |
No |
| Means |
Brain Sciences |
| Scope |
Article |
| Nature |
Científica |
| JCR Quartile |
3 |
| SJR Quartile |
3 |
| JCR Impact |
3.333 |
| SJR Impact |
0.727 |
| Web |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104935382&doi=10.3390%2fbrainsci11040516&partnerID=40&md5=1eb0860df7a1b2fca6c42b6f9e099e1a |
| Publication date |
19/04/2021 |
| ISI |
000642801500001 |
| Scopus Id |
2-s2.0-85104935382 |
| DOI |
10.3390/brainsci11040516 |
| Abstract |
This paper tackles the complex issue of detecting and classifying epileptic seizures whilst maintaining the total calculations at a minimum. Where many systems depend on the coupling between multiple sources, leading to hundreds of combinations of electrodes, our method calculates the instantaneous phase between non-identical upper and lower envelopes of a single-electroencephalography channel reducing the workload to the total number of electrode points. From over 600 h of simulations, our method shows a sensitivity and specificity of 100% for high false-positive rates and 83% and 75%, respectively, for moderate to low false positive rates, which compares well to both single- and multi-channel-based methods. Furthermore, pre-ictal variations in synchronisation were detected in over 90% of patients implying a possible prediction system. |
| Keywords |
epilepsy; synchronisation; envelope; DSP; hilbert transform; detection; Alzheimer disease; Parkinsons disease; prediction |
| Universidad Loyola members |
|
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