New feature extraction approach for epileptic EEG signal detection using time-frequency distributions.
This paper describes a new method to identify seizures in electroencephalogram (EEG) signals using feature extraction in time-frequency distributions (TFDs). Particularly, the method extracts features from the Smoothed Pseudo Wigner-Ville distribution using tracks estimated from the McAulay-Quatieri...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 48; no. 4; pp. 321 - 331 |
|---|---|
| Autores principales: | , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Apr2010
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104909085&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104909085 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Apr2010 vid: 48 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104909085 NLM20217264 2010595645 10.1007/s11517-010-0590-5 NLM20217264 104909085 ppf: 321 ppct: 10 formats: fmt: @attributes: type: P tig: atl: New feature extraction approach for epileptic EEG signal detection using time-frequency distributions. aug: au: Guerrero-Mosquera C Malanda Trigueros A Iriarte Franco J Navia-Vázquez A Guerrero-Mosquera, Carlos Trigueros, Armando Malanda Franco, Jorge Iriarte Navia-Vázquez, Angel affil: Signal Processing and Communications Department, University Carlos III of Madrid, Madrid, Spain sug: subj: Epilepsy, Partial Diagnosis Models, Biological Signal Processing, Computer Assisted Adult Artifacts Electroencephalography Methods Epilepsy, Partial Physiopathology Human Sensitivity and Specificity Adult: 19-44 years ab: This paper describes a new method to identify seizures in electroencephalogram (EEG) signals using feature extraction in time-frequency distributions (TFDs). Particularly, the method extracts features from the Smoothed Pseudo Wigner-Ville distribution using tracks estimated from the McAulay-Quatieri sinusoidal model. The proposed features are the length, frequency, and energy of the principal track. We evaluate the proposed scheme using several datasets and we compute sensitivity, specificity, F-score, receiver operating characteristics (ROC) curve, and percentile bootstrap confidence to conclude that the proposed scheme generalizes well and is a suitable approach for automatic seizure detection at a moderate cost, also opening the possibility of formulating new criteria to detect, classify or analyze abnormal EEGs. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|