EEG transient event detection and classification using association rules
| dc.contributor.author | Exarchos, T. P. | en |
| dc.contributor.author | Tzallas, A. T. | en |
| dc.contributor.author | Fotiadis, D. I. | en |
| dc.contributor.author | Konitsiotis, S. | en |
| dc.contributor.author | Giannopoulos, S. | en |
| dc.date.accessioned | 2015-11-24T17:33:21Z | |
| dc.date.available | 2015-11-24T17:33:21Z | |
| dc.identifier.issn | 1089-7771 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/13850 | |
| dc.rights | Default Licence | - |
| dc.subject | association rules | en |
| dc.subject | clustering | en |
| dc.subject | electroencephalographic (eeg) | en |
| dc.subject | epilepsy | en |
| dc.subject | spike detection | en |
| dc.subject | transient events | en |
| dc.subject | artificial neural-network | en |
| dc.subject | epileptiform discharges | en |
| dc.subject | interictal spikes | en |
| dc.subject | wave-form | en |
| dc.subject | selection | en |
| dc.subject | system | en |
| dc.title | EEG transient event detection and classification using association rules | en |
| heal.abstract | In this paper, a methodology for the automated detection and classification of transient events in electroencephalographic (EEG) recordings is presented. It is based on association rule mining and classifies transient events into four categories: epileptic spikes, muscle activity, eye blinking activity, and sharp alpha activity. The methodology involves four stages: 1) transient event detection; 2) clustering of transient events and feature extraction; 3) feature discretization and feature subset selection; and 4) association rule mining and classification of transient events. The methodology is evaluated using 25 EEG recordings, and the best obtained accuracy was 87.38%. The proposed approach combines high accuracy with the ability to provide interpretation for the decisions made, since it is based on a set of association rules. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | Doi 10.1109/Titb.2006.872067 | - |
| heal.identifier.secondary | <Go to ISI>://000239033000004 | - |
| heal.journalName | Ieee Transactions on Information Technology in Biomedicine | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2006 | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικών | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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