Matic--an intracardiac tachycardia classification system.
The use of an additional atrial sensing electrode together with a morphology recognition algorithm provides a significant improvement in classification performance over the current rate based algorithms used in implantable cardioverter defibrillator (ICD) devices, The classification system, called m...
| Publicado en: | Pacing & Clinical Electrophysiology Vol. 15; no. 9; pp. 1317 - 1332 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
Sep1992
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| 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=106087016&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 106087016 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01478389 4F8 jtl: Pacing & Clinical Electrophysiology issn: 01478389 maglogo: Y pubinfo: dt: Sep1992 vid: 15 iid: 9 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 106087016 2009413215 NLM1383991 106087016 ppf: 1317 ppct: 15 formats: fmt: @attributes: type: P tig: atl: Matic--an intracardiac tachycardia classification system. aug: au: Heng P Leong W Jabri MA sug: subj: Tachycardia, Ventricular Classification Defibrillators, Implantable Electrocardiography Neural Networks (Computer) Reoperation Tachycardia, Ventricular Physiopathology Tachycardia, Ventricular Therapy ab: The use of an additional atrial sensing electrode together with a morphology recognition algorithm provides a significant improvement in classification performance over the current rate based algorithms used in implantable cardioverter defibrillator (ICD) devices, The classification system, called morphology and timing intracardiac classifier (MATIC), follows a classification process similar to that used by cardiologists. Timing between the atrial and ventricular channels is examined using a decision tree and forms the primary criterion for arrhythmia classification. A neural network based morphology classifier is used for cases such as ventricular tachycardia with 1:1 retrograde conduction where timing alone cannot make a reliable decision. MATIC achieves 99.6% correct classification on a database of intracardiac electrogram (ICEG) signals containing 12,483 QRS complexes recorded from 67 patients during electrophysiological studies. Arrhythmias in this database include sinus tuchycardia, normal sin us rhythm, normal sinus rhythm with bundle branch block, sinus tachycardia with bundle branch block, atrial fibrillation (AF), various supraventricular tachycardias, ventricular tachycardia, ventricular tachycardia with 1:2 retrograde conduction, and ventricular fibrillation. Within these arrhythmias. there were numerous ventricular ectopic beats, fusion beats, noise, and other artifacts. MATIC addresses the classification problem from start to finish, inputs being raw intracardiac electrogram signals and the outputs being the recommended ICD therapy. Results achieved with MATIC were compared with a classifier used in the Telectronics Guardian ATP 4210, which achieved 75.9% correct classification on the same database. MATIC is simple and efficient, making it suitable for use in a low power implantable device. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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