Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

Anant, Kanwaldip S.

doi:10.2172/611772

Cited by 3 publications

(2 citation statements)

References 49 publications

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“…The function has a finite energy (oN). Most researchers (e.g., Salimath, 2011;Jordan and Kiksad, 1997;Smith, 1999;Abid et al, 2007;Thiebaut and Roques, 2005;Antonie et al, 2000, andAnant, 1997) agree on this condition while Kumar and Foufoula-Georgiou (1997), Torrence and Compo (1998), Senhadji and Wendling (2002), and Plett (2007) recommended that the mother wavelet has a unit energy; i.e., Z 1 À1…”

Section: Mathematical Backgroundmentioning

confidence: 99%

Analysis of wave slam induced hull vibrations using continuous wavelet transforms

et al. 2013

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Section: Mathematical Backgroundmentioning

confidence: 99%

Analysis of wave slam induced hull vibrations using continuous wavelet transforms

et al. 2013

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“…Prior literature on wavelet decomposition of the IEGM refers only to the Daubechies orthogonal transforms, and usually only the Haar transform (Murray, 1993;Batista, 1995;Zaffram, 1996;Anant, 1997;McClure, 1997;Azzam, 1998). proportional to their increased filter length.…”

Section: Advantages Of the Integer-based Lifting Line Waveletmentioning

confidence: 99%

Wavelet Based Feature Extraction and Dimension Reduction for the Classification of Human Cardiac Electrogram Depolarization Waveforms

Voir¹

2000

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An abstract of the thesis of Cluistopher S. De Voir for the Master of Science in Electrical and Computer Engineering presented October 04, 2005. Title: Wavelet based feature extraction and dimension reduction for the classification of human cardiac electrogram depolarization waveforms.An essential task for a pacemaker or implantable defibrillator is the accurate identification of rhythm categories so that the correct electrotherapy can be administered. Because some rhythms cause a rapid dangerous drop in cardiac output, it is necessary to categorize depolarization waveforms on a beat-to-beat basis to accomplish rhythm classification as rapidly as possible. In this thesis, a depolarization waveform classifier based on the Lifting Line Wavelet Transform is described. It overcomes problems in existing rate-based event classifiers; namely, (1) they are insensitive to the conduction path of the heart rhythm and (2) they are not robust to pseudo-events. The performance of the Lifting Line Wavelet Transform based classifier is illustrated with representative examples. Although rate based methods of event categorization have served well in implanted devices, these methods suffer in sensitivity and specificity when atrial, and 2 ventricular rates are similar. Human experts differentiate rhythms by morphological features of strip chart electrocardiograms. The wavelet transform is a simple approximation of this human expert analysis function because it correlates distinct morphological features at multiple scales. The accuracy of implanted rhythm determination can then be improved by using human-appreciable time domain features enhanced by time scale decomposition of depolarization waveforms.The purpose of the present work was to determine the feasibility of implementing such a system on a limited-resolution platform. 78 patient recordings were split into equal segments of reference, confirmation, and evaluation sets. Each recording had a sampling rate of 512Hz, and a significant change in rhythm in the recording. The wavelet feature generator implemented in Matlab performs anti-alias pre-filtering, quantization, and threshold-based event detection, to produce indications of events to submit to wavelet transformation. The receiver operating characteristic curve was used to rank the discriminating power of the feature accomplishing dimension reduction. Accuracy was used to confirm the feature choice. Evaluation accuracy was greater than or equal to 95% over the IEGM recordings.

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A Wavelet-Based Approach for Online External Leakage Diagnosis and Isolation from Internal Leakage in Hydraulic Actuators

Goharrizi¹,

Sepehri²,

Wu³

2011

International Journal of Fluid Power

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Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram

Cited by 3 publications

References 49 publications

Analysis of wave slam induced hull vibrations using continuous wavelet transforms

Analysis of wave slam induced hull vibrations using continuous wavelet transforms

Wavelet Based Feature Extraction and Dimension Reduction for the Classification of Human Cardiac Electrogram Depolarization Waveforms

A Wavelet-Based Approach for Online External Leakage Diagnosis and Isolation from Internal Leakage in Hydraulic Actuators

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