Detection and identification of cardiac arrhythmias using an adaptive, linear-predictive filter

Author

Finelli, C.J. ; Jenkins, J.M. ; DiCarlo, L.A.

Author_Institution

GMI Eng. & Manage. Inst., Flint, MI, USA

fYear

1993

fDate

5-8 Sep 1993

Firstpage

177

Lastpage

180

Abstract

In order to detect an abrupt change in morphology of intracardiac electrograms, the authors have developed a supplemental algorithm to rate criteria which utilizes the mean-squared error of an adaptive, linear-predictive filter (ALPF). Further analysis of the filter error is invoked when such a change is detected to identify the rhythm. ALPF successfully identified 10/11 (91%) cases of ventricular tachycardia (VT), 6/8 (75%) cases of ventricular fibrillation (VF), and 4/4 (100%) cases of sinus tachycardia (ST). As a basis of comparative analysis, correlation waveform analysis (CWA) was used to identify the same test set of arrhythmias. CWA correctly identified 11/11 (100%) cases of VT, 4/8 (50%) cases of VF, and 4/4 (100%) cases of ST. When compared to CWA, ALPF has similar accuracy in differentiating VT and ST. ALPF appears to be superior to CWA in identifying VF

Keywords

adaptive filters; electrocardiography; medical signal processing; waveform analysis; abrupt morphology change; adaptive linear-predictive filter; cardiac arrhythmias detection; cardiac arrhythmias identification; correlation waveform analysis; mean-squared error; sinus tachycardia; supplemental algorithm; ventricular fibrillation; ventricular tachycardia; Adaptive filters; Change detection algorithms; Engineering management; Error correction; Fibrillation; Morphology; Rhythm; Strontium; Testing; Thyristors;

fLanguage

English

Publisher

ieee

Conference_Titel

Computers in Cardiology 1993, Proceedings.

Conference_Location

London

Print_ISBN

0-8186-5470-8

Type

conf

DOI

10.1109/CIC.1993.378475

Filename

378475