On two weighted signal averaging methods and their application to the surface detection of cardiac micropotentials

Zhong, Jicun; Lü, Wenzhong

doi:10.1016/0010-4809(91)90033-s

Cited by 11 publications

(1 citation statement)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this method, a beat is rejected if its noise level is significantly greater than the mean of the noise levels of all beats previously accepted into the averaging process. c) Weighted averaging (WA): each beat is multiplied by a coefficient inversely proportional to its noise variance [3].…”

Section: Modeled Asmentioning

confidence: 99%

An improved weighted signal averaging method for high-resolution ECG signals

Laciar

Jané²

Computers in Cardiology 2001. Vol.28 (Cat. No.01CH37287)

View full text Add to dashboard Cite

In this paper, we propose a new technique to estimate the coeficients for the weighted averaging of highresolution ECG (HRECG) records. The purpose of this study was to minimize the number of beats to average in records contaminated with non-stationary noise.The following averaging methods were studied: I ) Linear averaging of all beats (LA), 2) Linear averaging rejecting very noisy beats (RA) and 3) Weighted averaging (WA). For WA, two techniques for noise variance estimation in each beat were analyzed: a) A noise estimation in a 60 ms window on ST segment (WA-W) and b) A new algorithm that estimates the noise variance from the difference signal obtained by subtracting the averaged beat from the individual beat(WA-D). All methods were tested in simulated HRECG records, contaminated with several types of noise.We conclude that WA methods minimizes the number of averaged beats compared with LA and RA methods in situations of non-stationary noise. However, the proposed WA-D method shows a higher effectiveness than WA-W method due to a better estimation of the noise variance in individual beats.

show abstract

Section: Modeled Asmentioning

confidence: 99%

An improved weighted signal averaging method for high-resolution ECG signals

Laciar

Jané²

Computers in Cardiology 2001. Vol.28 (Cat. No.01CH37287)

View full text Add to dashboard Cite

show abstract

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

Laguna

Moody

García

et al. 1999

Med. Biol. Eng. Comput.

View full text Add to dashboard Cite

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.

show abstract