Literature DB >> 6453670

Redundancy reduction for improved display and analysis of body surface potential maps. II. Temporal compression.

A K Evans, R L Lux, M J Burgess, R F Wyatt, J A Abildskov.   

Abstract

This paper describes use of the Karhunen-Loeve expansion to identify and reduce temporal redundancy in electrocardiographic body surface potential maps (192 body surface leads recorded simultaneously at 1 kHz/channel for approximately 600 msec). Temporal data compression of about 20 to 1 was obtained with accurate representation of the original data. Use of separate sets of orthonormal basis functions for QRS and ST-T provided a more accurate representation than the basis derived from QRST. Combined with the spatial compression described in the preceding paper, overall map data compression of about 320 to 1 was obtained without significant loss of accuracy of representation or map appearance. With both spatial and temporal compression the 100,000 numbers which typically comprise a single cardiac complex were accurately represented by 216 coefficients. Using basis functions derived from a single cardiac complex were accurately represented by 216 coefficients. Using basis functions derived from a training set of 221 maps, the estimated average rms error of representation was 60 microV during the ST-T. For 34 test maps which were not part of the training set, measured average errors were 64 microV during the QRS and 23 microV during the ST-T. This technique provides a basis for quantification of the diagnostic content of maps and automated classification of maps.

Mesh:

Year:  1981        PMID: 6453670     DOI: 10.1161/01.res.49.1.197

Source DB:  PubMed          Journal:  Circ Res        ISSN: 0009-7330            Impact factor:   17.367


  7 in total

1.  Conservation and characterisation of spatial features in a new method of data compression for body surface potential maps.

Authors:  S Gilat; D Adam
Journal:  Med Biol Eng Comput       Date:  1992-01       Impact factor: 2.602

2.  Orthogonal expansions: their applicability to signal extraction in electrophysiological mapping data.

Authors:  R Lamothe; G Stroink
Journal:  Med Biol Eng Comput       Date:  1991-09       Impact factor: 2.602

3.  Spatial, temporal and wavefront direction characteristics of 12-lead T-wave morphology.

Authors:  B Acar; G Yi; K Hnatkova; M Malik
Journal:  Med Biol Eng Comput       Date:  1999-09       Impact factor: 2.602

4.  MANIFOLD LEARNING FOR ANALYSIS OF LOW-ORDER NONLINEAR DYNAMICS IN HIGH-DIMENSIONAL ELECTROCARDIOGRAPHIC SIGNALS.

Authors:  B Erem; P Stovicek; D H Brooks
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2012-07-12

Review 5.  Electrocardiographic body surface mapping: potential tool for the detection of transient myocardial ischemia in the 21st century?

Authors:  Monique R Robinson; Nicholas Curzen
Journal:  Ann Noninvasive Electrocardiol       Date:  2009-04       Impact factor: 1.468

6.  The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity.

Authors:  Ali S Rababah; Laura R Bear; Yesim Serinagaoglu Dogrusoz; Wilson Good; Jake Bergquist; Job Stoks; Rob MacLeod; Khaled Rjoob; Michael Jennings; James Mclaughlin; Dewar D Finlay
Journal:  Comput Biol Med       Date:  2021-07-21       Impact factor: 6.698

7.  Non-ST-Segment Elevation Myocardial Infarction: A Novel and Robust Approach for Early Detection of Patients at Risk.

Authors:  Robert L Lux
Journal:  J Am Heart Assoc       Date:  2015-07-24       Impact factor: 5.501

  7 in total

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