EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/11/4/516 |
| _version_ | 1797537190904856576 |
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| author | James Brian Romaine Mario Pereira Martín José Ramón Salvador Ortiz José María Manzano Crespo |
| author_facet | James Brian Romaine Mario Pereira Martín José Ramón Salvador Ortiz José María Manzano Crespo |
| author_sort | James Brian Romaine |
| collection | DOAJ |
| description | 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 <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>100</mn><mo>%</mo></mrow></semantics></math></inline-formula> for high false-positive rates and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>83</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>75</mn><mo>%</mo></mrow></semantics></math></inline-formula>, 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 <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>90</mn><mo>%</mo></mrow></semantics></math></inline-formula> of patients implying a possible prediction system. |
| first_indexed | 2024-03-10T12:12:34Z |
| format | Article |
| id | doaj.art-6e72983825654116a38706a7313a99e1 |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-03-10T12:12:34Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-6e72983825654116a38706a7313a99e12023-11-21T16:07:43ZengMDPI AGBrain Sciences2076-34252021-04-0111451610.3390/brainsci11040516EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and PredictionJames Brian Romaine0Mario Pereira Martín1José Ramón Salvador Ortiz2José María Manzano Crespo3Departamento Ingenería, Universidad Loyola Andalucía, Dos Hermanas, 41704 Seville, SpainDepartamento Ingenería, Universidad Loyola Andalucía, Dos Hermanas, 41704 Seville, SpainDepartamento Ingenería, Universidad Loyola Andalucía, Dos Hermanas, 41704 Seville, SpainDepartamento Ingenería, Universidad Loyola Andalucía, Dos Hermanas, 41704 Seville, SpainThis 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 <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>100</mn><mo>%</mo></mrow></semantics></math></inline-formula> for high false-positive rates and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>83</mn><mo>%</mo></mrow></semantics></math></inline-formula> and <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>75</mn><mo>%</mo></mrow></semantics></math></inline-formula>, 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 <inline-formula><math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mn>90</mn><mo>%</mo></mrow></semantics></math></inline-formula> of patients implying a possible prediction system.https://www.mdpi.com/2076-3425/11/4/516epilepsysynchronisationenvelopeDSPhilbert transformdetection |
| spellingShingle | James Brian Romaine Mario Pereira Martín José Ramón Salvador Ortiz José María Manzano Crespo EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction Brain Sciences epilepsy synchronisation envelope DSP hilbert transform detection |
| title | EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| title_full | EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| title_fullStr | EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| title_full_unstemmed | EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| title_short | EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction |
| title_sort | eeg single channel envelope synchronisation and classification for seizure detection and prediction |
| topic | epilepsy synchronisation envelope DSP hilbert transform detection |
| url | https://www.mdpi.com/2076-3425/11/4/516 |
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