Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy
Permutation entropy (PE) has been widely exploited to measure the complexity of the electroencephalogram (EEG), especially when complexity is linked to diagnostic information embedded in the EEG. Recently, the authors proposed a spatial-temporal analysis of the EEG recordings of absence epilepsy pat...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-07-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/17/7/4627 |
| _version_ | 1798040548611719168 |
|---|---|
| author | Nadia Mammone Jonas Duun-Henriksen Troels W. Kjaer Francesco C. Morabito |
| author_facet | Nadia Mammone Jonas Duun-Henriksen Troels W. Kjaer Francesco C. Morabito |
| author_sort | Nadia Mammone |
| collection | DOAJ |
| description | Permutation entropy (PE) has been widely exploited to measure the complexity of the electroencephalogram (EEG), especially when complexity is linked to diagnostic information embedded in the EEG. Recently, the authors proposed a spatial-temporal analysis of the EEG recordings of absence epilepsy patients based on PE. The goal here is to improve the ability of PE in discriminating interictal states from ictal states in absence seizure EEG. For this purpose, a parametrical definition of permutation entropy is introduced here in the field of epileptic EEG analysis: the permutation Rényi entropy (PEr). PEr has been extensively tested against PE by tuning the involved parameters (order, delay time and alpha). The achieved results demonstrate that PEr outperforms PE, as there is a statistically-significant, wider gap between the PEr levels during the interictal states and PEr levels observed in the ictal states compared to PE. PEr also outperformed PE as the input to a classifier aimed at discriminating interictal from ictal states. |
| first_indexed | 2024-04-11T22:09:09Z |
| format | Article |
| id | doaj.art-bb95e9753a6046999b7f190a0fb09027 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T22:09:09Z |
| publishDate | 2015-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-bb95e9753a6046999b7f190a0fb090272022-12-22T04:00:37ZengMDPI AGEntropy1099-43002015-07-011774627464310.3390/e17074627e17074627Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi EntropyNadia Mammone0Jonas Duun-Henriksen1Troels W. Kjaer2Francesco C. Morabito3IRCCS Centro Neurolesi Bonino-Pulejo, Via Palermo c/da Casazza, SS. 113, Messina, ItalyHypoSafe A/S, Diplomvej 381, 2800 Kgs. Lyngby, DenmarkNeurophysiology Center, Department of Neurology, Roskilde University Hospital, Koegevej 7-13, DK-4000 Roskilde, DenmarkDICEAM Department, Mediterranean University of Reggio Calabria, Via Graziella Feo di Vito, 89060 Reggio Calabria, ItalyPermutation entropy (PE) has been widely exploited to measure the complexity of the electroencephalogram (EEG), especially when complexity is linked to diagnostic information embedded in the EEG. Recently, the authors proposed a spatial-temporal analysis of the EEG recordings of absence epilepsy patients based on PE. The goal here is to improve the ability of PE in discriminating interictal states from ictal states in absence seizure EEG. For this purpose, a parametrical definition of permutation entropy is introduced here in the field of epileptic EEG analysis: the permutation Rényi entropy (PEr). PEr has been extensively tested against PE by tuning the involved parameters (order, delay time and alpha). The achieved results demonstrate that PEr outperforms PE, as there is a statistically-significant, wider gap between the PEr levels during the interictal states and PEr levels observed in the ictal states compared to PE. PEr also outperformed PE as the input to a classifier aimed at discriminating interictal from ictal states.http://www.mdpi.com/1099-4300/17/7/4627permutation entropyelectroencephalogramRényi’s entropyabsence seizures |
| spellingShingle | Nadia Mammone Jonas Duun-Henriksen Troels W. Kjaer Francesco C. Morabito Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy Entropy permutation entropy electroencephalogram Rényi’s entropy absence seizures |
| title | Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy |
| title_full | Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy |
| title_fullStr | Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy |
| title_full_unstemmed | Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy |
| title_short | Differentiating Interictal and Ictal States in Childhood Absence Epilepsy through Permutation Rényi Entropy |
| title_sort | differentiating interictal and ictal states in childhood absence epilepsy through permutation renyi entropy |
| topic | permutation entropy electroencephalogram Rényi’s entropy absence seizures |
| url | http://www.mdpi.com/1099-4300/17/7/4627 |
| work_keys_str_mv | AT nadiamammone differentiatinginterictalandictalstatesinchildhoodabsenceepilepsythroughpermutationrenyientropy AT jonasduunhenriksen differentiatinginterictalandictalstatesinchildhoodabsenceepilepsythroughpermutationrenyientropy AT troelswkjaer differentiatinginterictalandictalstatesinchildhoodabsenceepilepsythroughpermutationrenyientropy AT francescocmorabito differentiatinginterictalandictalstatesinchildhoodabsenceepilepsythroughpermutationrenyientropy |