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A Study of the Technology in the Detection of Microsoft T-wave Alternans

Author: ChenTianTian
Tutor: ZhaoJie
School: Shandong Normal University
Course: Signal and Information Processing
Keywords: ECG T-wave alternans Poincare scatter spectral method synthetic ECGs
CLC: TN911.7
Type: Master's thesis
Year: 2014
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Abstract


As one of the most dangerous killer in the world, cardiovascular disease has drawn greatattention of human. T-wave Alternans (TWA) is a cardiac electron variational phenomenon, itreflects that T-wave morphology, polarity and amplitude occur beat to beat alternans. Studies inrecent30years have shown that the TWA test can predict which patients were at highest risk forsudden cardiac death or malignant arrhythmias. Once the Visible TWA appears, the symptomoften turns to ventricular fibrillation and sudden death. So its predictive value is not high.Microsoft T-wave Alternans (MTWA) can’t be observed in electrocardiogram. It is of greatsignificance for predicting malignant arrhythmias and avoiding sudden death through digitalsignal processing technology to detect MTWA.This thesis focus on the detection of TWA, the main body of the research were as follows:First is preprocessing for ECG signals. We used simple integer coefficient notch filter,linear phase FIR digital filtering, wavelet decomposition and reconstruction theory and theimproved threshold algorithm for ECG filtering processing to remove power-line interference,baseline wander and muscle power interference. Then, We used Marr wavelet which has theadvantage of accurate positioning and simple calculation, based on a-trous algorithm, todemarcate ECG characteristic points. Finally, we searched the T wave peak after the S wavepeak within a certain range. The above lay the foundation for future studies of ECG.The second is the study of TWA detection algorithm. First, we selected128continuous Twaves using improved T-wave window analysis method, and aligned them with T-wave peak.After getting7location points by synchronization sampling of each of the T-wave, T-wavematrix and T-wave sampling point sequence was constructed. Secondly, Spectral method wasused for detection. It turned the amplitude alternans into normalized spectrum by fast Fouriertransform. Subtracting the background noise, the value of spectrum at the0.5cbp was used tocalculate the average amplitude of TWA (Vtwa) which is the index to judge whether the TWAexisted. Finally, Poincare scatter was used for detection. The first difference sequence to theT-wave sampling series was used to draw a Poincare scatter. We have analysed the relationshipbetween the graphic mode of Poincare scatter and T-wave alternans, and proposed the ‘horizontalsearch algorithm’ to complete graphic processing. Then, based on the shape of Poincare scatter,we proposed three quantitative parameters of Poincare scatter: Short_axis, Long_axis andAxial_ratio. This paper took Axial_ratio as the final index and selected an appropriate thresholdvalue to recognize TWA.The third is the simulation analysis. In order to provide an objective assessment of TWAanalysis methods, by designing a simulation system, we got synthetic electrocardiogram (ECG)which has different T-wave morphology, amplitude and signal-to-noise ratio. Then, the algorithmsensitivity, accuracy, specificity and positive predictivity were obtained by simulation analysis.In addition, through the simulation experiment of the clinical data from authoritative database,we have verified the feasibility and effectiveness of Poincare scatter method to detect TWA afteranalyzing the test results of two methods.Overall, Poincare scatter method is a new feasible method. It is intuitive, simple calculationand no high quality signal requirements. Besides, it has stronger anti-interference ability, not only can measure the magnitude of the T-wave alternans, but also contains time-domaininformation. However, researches on TWA detection with Poincare scatter method are notcommon in worldwide. We need more data analysis to improve the algorithm, and its applicationprospect also needs further clinical testing.

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