Literature DB >> 10396821

Analysis of the ST-T complex of the electrocardiogram using the Karhunen--Loève transform: adaptive monitoring and alternans detection.

P Laguna1, G B Moody, J García, A L Goldberger, R G Mark.   

Abstract

The Karhunen-Loève transform (KLT) is applied to study the ventricular repolarisation period as reflected in the ST-T complex of the surface ECG. The KLT coefficients provide a sensitive means of quantitating ST-T shapes. A training set of ST-T complexes is used to derive a set of KLT basis vectors that permits representation of 90% of the signal energy using four KLT coefficients. As a truncated KLT expansion tends to favor representation of the signal over any additive noise, a time series of KLT coefficients obtained from successive ST-T complexes is better suited for representation of both medium-term variations (such as ischemic changes) and short-term variations (such as ST-T alternans) than discrete parameters such as the ST level or other local indices. For analysis of ischemic changes, an adaptive filter is described that can be used to estimate the KLT coefficient, yielding an increase in the signal-to-noise ratio of 10 dB (u = 0.1), with a convergence time of about three beats. A beat spectrum of the unfiltered KLT coefficient series is used for detection of ST-T alterans. These methods are illustrated with examples from the European ST-T Database. About 20% of records revealed quasi-periodic salvos of ischemic ST-T change episodes and another 20% exhibit repetitive, but not clearly periodic patterns of ST-T change episodes. About 5% of ischemic episodes were associated with ST-T alterans.

Entities:  

Keywords:  NASA Discipline Cardiopulmonary; Non-NASA Center

Mesh:

Year:  1999        PMID: 10396821     DOI: 10.1007/bf02513285

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  21 in total

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Journal:  IEEE Trans Biomed Eng       Date:  1991-06       Impact factor: 4.538

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7.  A segmental polynomial model of ventricular electrograms as a simple and efficient morphology discriminator for implantable devices.

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