Correlation method versus enhanced modified moving average method for automatic detection of T-wave alternans

2010 ◽  
Vol 98 (1) ◽  
pp. 94-102 ◽  
Author(s):  
Laura Burattini ◽  
Silvia Bini ◽  
Roberto Burattini
Keyword(s):  
Average Method ◽  
Moving Average ◽  
Correlation Method ◽  
Automatic Detection ◽  
T Wave ◽  
T Wave Alternans

scholarly journals Microvolt T-wave Alternans: Where Are We Now?

2016 ◽  
Vol 5 (1) ◽  
pp. 37 ◽  
Author(s):  
Aapo L Aro ◽  
◽  
Tuomas V Kenttä ◽  
Heikki V Huikuri ◽  
◽  
...  
Keyword(s):  
Average Method ◽  
Ventricular Arrhythmias ◽  
Moving Average ◽  
Cardiovascular Death ◽  
Left Ventricular ◽  
Sufficient Evidence ◽  
T Wave ◽  
T Wave Alternans ◽  
The Time Domain ◽  
Important Marker

Microvolt T-wave alternans (TWA), characterised as beat-to-beat fluctuation of T-wave amplitude and morphology, is an electrophysiological phenomenon associated clinically with impending ventricular arrhythmias and is an important marker of arrhythmia risk. Currently, two main methods for the detection of TWA exist, namely, the spectral method and the time-domain modified moving average method; both are discussed in this review. Microvolt TWA has been associated with cardiovascular mortality and sudden cardiac death in several clinical studies involving >14,000 subjects with reduced as well as preserved left ventricular function. Although TWA appears to be a useful marker of susceptibility for lethal ventricular arrhythmias and cardiovascular death, so far there is no sufficient evidence from randomised clinical trials to support its use in guiding therapy. However, several ongoing trials are expected to provide more information about the clinical use of TWA testing.

scholarly journals Modified moving average analysis of T-wave alternans to predict ventricular fibrillation with high accuracy

2002 ◽  
Vol 92 (2) ◽  
pp. 541-549 ◽  
Author(s):  
Bruce D. Nearing ◽  
Richard L. Verrier
Keyword(s):  
Ventricular Fibrillation ◽  
Moving Average ◽  
Motion Artifact ◽  
Accurate Estimate ◽  
T Wave ◽  
Average Analysis ◽  
Experimental Laboratory ◽  
Nonstationary Data ◽  
T Wave Alternans ◽  
And Performance

T-wave alternans is a marker of cardiac electrical instability with the potential for arrhythmia risk stratification. The modified moving average method was developed to measure alternans in settings with artifacts, noise, and nonstationary data. Algorithms were developed and performance characteristics were validated with simulated electrocardiograms (ECGs). Experimental laboratory ECGs with dynamically changing alternans values were analyzed. Alternans values estimated by modified moving average analysis correlated strongly with input alternans values ( r 2 = 0.9999). Rapidly changing alternans levels and phase reversals did not perturb the measurement. When heart rate was increased from 60 to 180 beats/min, with T-wave alternans apex moving from 237 to 103 ms after the R wave, the measured alternans peak varied <5% from input value. Simulated 50- to 1,000-μV motion artifact spikes typical of treadmill ECGs produced inaccuracies <2%. Alternans values in experimental laboratory study using standard electrodes tracked vulnerability to myocardial ischemia-induced ventricular fibrillation with 100% sensitivity and specificity at a cut point of 0.75 mV. Modified moving average analysis is a robust method that precisely measures T-wave alternans in settings with artifacts, noise, and nonstationary data typical of clinical ECGs and yields an accurate estimate of risk for ventricular fibrillation.

A MODIFIED CORRELATION METHOD FOR T-WAVE ALTERNANS DETECTION

2013 ◽  
Vol 25 (03) ◽  
pp. 1350030
Author(s):  
Xiangkui Wan ◽  
Kanghui Yan ◽  
Minggui Li ◽  
Dingcheng Xiang
Keyword(s):  
Heart Diseases ◽  
Correlation Method ◽  
Absolute Difference ◽  
T Wave ◽  
Formidable Challenge ◽  
Maximum Absolute Difference ◽  
T Wave Alternans ◽  
Improved Performance ◽  
The Time Domain ◽  
Electrocardiogram Ecg

Identification of individuals who are at risk for sudden cardiac death (SCD) remains a formidable challenge. T-wave alternans (TWA) evaluation is emerging as an important tool for risk stratification in patients with heart diseases. Several methods have been developed in recent years to detect and quantify TWA. One such method is known as the correlation method (CM). This method performs well for different levels of TWA and phase shifts in the time domain, but it is sensitive to noise and requires higher quality of electrocardiogram (ECG) signal for test. In this paper, we propose a modified correlation method (MCM) to ensure a robust and accuracy detection of TWA. Compared with CM, MCM add a stage of T-wave curve fitting before media T-wave template, and the TWA magnitude is obtained by meaning the maximum absolute difference between even and odd T-wave. Our assessment study demonstrates the improved performance of the proposed algorithm.

scholarly journals A Time-Domain Hybrid Analysis Method for Detecting and Quantifying T-Wave Alternans

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xiangkui Wan ◽  
Kanghui Yan ◽  
Linlin Zhang ◽  
Yanjun Zeng
Keyword(s):  
Time Domain ◽  
Correlation Method ◽  
Filter Method ◽  
Least Squares Regression ◽  
Analysis Method ◽  
Hybrid Analysis ◽  
Match Filter ◽  
T Wave ◽  
Increased Risk ◽  
T Wave Alternans

T-wave alternans (TWA) in surface electrocardiograph (ECG) signals has been recognized as a marker of cardiac electrical instability and is hypothesized to be associated with increased risk for ventricular arrhythmias among patients. A novel time-domain TWA hybrid analysis method (HAM) utilizing the correlation method and least squares regression technique is described in this paper. Simulated ECGs containing artificial TWA (cases of absence of TWA and presence of stationary or time-varying or phase-reversal TWA) under different baseline wanderings are used to test the method, and the results show that HAM has a better ability of quantifying TWA amplitude compared with the correlation method (CM) and adapting match filter method (AMFM). The HAM is subsequently used to analyze the clinical ECGs, and results produced by the HAM have, in general, demonstrated consistency with those produced by the CM and the AMFM, while the quantifying TWA amplitudes by the HAM are universally higher than those by the other two methods.

Detecting and Quantifying T Wave Alternans Using Linear Least Squares Curve Fitting Method

2012 ◽  
Vol 239-240 ◽  
pp. 1404-1408
Author(s):  
Xiang Kui Wan ◽  
Kang Hui Yan ◽  
Ming Gui Li
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Moving Average ◽  
Correlation Coefficients ◽  
Linear Least Squares ◽  
T Wave ◽  
Patients At Risk ◽  
Invasive Method ◽  
T Wave Alternans ◽  
Curve Fitting Method

Evaluatement of T-wave alternans (TWA) is a non-invasive method to identify patients at risk for sudden cardiac death. A novel time-domain algorithm based on linear least squares method (LSM) for TWA analysis is developed in this paper. And the LSM’s ability to TWA analaysis in comparison with the modified moving average (MMA) method was demonstrated. In a simulation study LSM and MMA can both detected TWA with high accuracy, but under lower SNR levels LSM was found more robust, and its evaluated TWA values are closer to true TWA value. The algorithm was subsequently used to analyze the clinical ECGs from T-Wave Alternans Challenge Database, which showed that the results from this method vs. MMA had the correlation coefficients of 0.89.

Detection of non-stationary T wave alternans: New correlation method compared to spectral method

1998 ◽  
Vol 31 ◽  
pp. 30
Author(s):  
Laura Burattini ◽  
Wojciech Zareba ◽  
Jean Philippe Coudere ◽  
Arthur J Moss
Keyword(s):  
Spectral Method ◽  
Correlation Method ◽  
T Wave ◽  
New Correlation ◽  
T Wave Alternans
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