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Advanced Signal Processing Applications of the ECG: T-Wave Alternans, Heart Rate Variability, and the Signal Averaged ECG

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Practical Signal and Image Processing in Clinical Cardiology

Abstract

A variety of advanced signal processing techniques are already used in contemporary ­cardiology practice, embedded in widely used commercial tools. This chapter focuses on three such ECG tools that have clinical trial data to support them and that have been incorporated into practice guidelines: T-wave alternans (TWA), heart rate variability (HRV), and the signal averaged ECG (SAECG). TWA is defined as alternate-beat fluctuations in the amplitude or morphology of the ECG T-wave, and reflects dispersion of repolarization.1 HRV is defined as fluctuations in the interval between consecutive sinus node-initiated beats, and indicates the balance of autonomic influences on the sinus node.2 The SAECG is derived from multiple beats, aligned by their QRS complexes and averaged to increase the signal-to-noise ratio, to reveal low amplitude signals typically produced by slow conduction.3 Each tool has been used for several purposes. However, the best validated applications are in predicting the risk for sudden cardiac arrest (SCA) from lethal ventricular arrhythmias, or the risk for major adverse cardiac events following myocardial infarction.

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Acknowledgement

Supported, in part, by grants to SMN from the Doris Duke Charitable Foundation and the National Heart, Lung, and Blood institute (HL 70529, HL83359).

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Correspondence to Ashwani P. Sastry .

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Sastry, A.P., Narayan, S.M. (2010). Advanced Signal Processing Applications of the ECG: T-Wave Alternans, Heart Rate Variability, and the Signal Averaged ECG. In: Goldberger, J., Ng, J. (eds) Practical Signal and Image Processing in Clinical Cardiology. Springer, London. https://doi.org/10.1007/978-1-84882-515-4_20

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