Wavelet transforms and the ECG: a review

Addison, Paul

doi:10.1088/0967-3334/26/5/r01

Cited by 712 publications

(374 citation statements)

References 113 publications

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“…For this reason, we have performed experiments to compare the compression ratio and the accuracy of different algorithms in biomedical signal processing. We used the review [10] as a reference of the ECG signal compressing methods. To assess the quality of the results, we performed our tests on the two main classes of the ECG compression algorithms.…”

Section: Methodsmentioning

confidence: 99%

RAIT: the Rational Approximation and Interpolation Toolbox for Matlab, with Experiments on ECG Signals

Kovács

Lócsi

2012

International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems

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Abstract-There is a wide range of applications of rational function systems. Including in system, control theories and signal processing. A special class of rational functions, the so-called Blaschke functions and the orthonormal Malmquist-Takenaka (MT) systems are effectively used for representing signals especially electrocardiograms.We present our project on a general MATLAB library for rational function systems and their applications. It contains Blaschke functions, MT systems and biorthogonal systems. We implemented not only the continuous but the discrete versions as well, since in applications the latter one is needed. The complex and real interpretations are both available. We also built in methods for finding the poles automatically. Also, some interactive GUIs were implemented for visual demonstration that help the users in understanding the roles of certain parameters such as poles, multiplicity etc.

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Section: Methodsmentioning

confidence: 99%

RAIT: the Rational Approximation and Interpolation Toolbox for Matlab, with Experiments on ECG Signals

Kovács

Lócsi

2012

International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems

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“…Analyzing the frequency content of the signal using wavelets can provide the frequency content of the two signals that is localized in time (Addison, 2005). The wavelet approach offers a targeted form of sensitivity analysis compared to the blanket approach using only lumped metrics.…”

Section: Parameter Behavior In the Frequency Domain (Via Wavelet Analmentioning

confidence: 99%

Multiple domain evaluation of watershed hydrology models

Kumarasamy

Belmont

2017

Preprint

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Abstract. Watershed scale models simulating hydrology and water quality have advanced rapidly in sophistication, process 5 representation, flexibility in model structure, and input data. Given the importance of these models to support decision-making for a wide range of environmental issues, the hydrology community is compelled to improve the metrics used to evaluate model performance. More targeted and comprehensive metrics will facilitate better and more efficient calibration and will help demonstrate that the model is useful for the intended purpose. Here we introduce a suite of new tools for model evaluation,packaged as an open-source Hydrologic Model Evaluation (HydroME) Toolbox. Specifically, we demonstrate the use of box 10 plots to illustrate the full distribution of common model performance metrics, such as R 2 , use of Euclidian distance, empirical Quantile-Quantile (Q-Q) plots and flow duration curves as simple metrics to identify and localize errors in model simulations.Further, we demonstrate the use of magnitude squared coherence to compare the frequency content between observed and modeled streamflow and wavelet coherence to localize frequency mismatches in time. We provide a rationale for a hierarchical selection of parameters to adjust during calibration and recommend that modelers progress from parameters with the most 15 uncertainty to the least uncertainty, namely starting with pure calibration parameters, followed by derived parameters, and finally measured parameters. We apply these techniques in the calibration and evaluation of models of two watersheds, the Le Sueur River Basin (2880 km 2 ) and Root River Basin (4300 km 2 ) in southern Minnesota, USA.

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“…Addison [8] has conducted a review of both continuous wavelet transform (CWT) and discrete wavelet transform (DWT) on ECG data, concluding that DWT is practically easy to use, while CWT -being more complex and difficult to tune parameters -is able to keep a high resolution in the time-frequency plane, which can result in more accurate identification of components. Another study in wavelet applications in the medical field was done by Pizurica et.…”

Section: Related Workmentioning

confidence: 99%

“…Wavelets compression techniques have since then been extensively used in image compression and are part of the JPEG 2000 standard [7]. Wavelet transforms have also been extensively used in medical data analysis including ECG diagnosis [8] and ultrasound image processing [9]. More recently, researchers have applied wavelet transforms in the field of Non-Intrusive Load Monitoring (NILM) [10,11].…”

Section: Introductionmentioning

confidence: 99%

Time Series Classification with Discrete Wavelet Transformed Data: Insights from an Empirical Study

Bissyandé

Klein

et al. 2016

International Conferences on Software Engineering and Knowledge Engineering

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Time series mining has become essential for extracting knowledge from the abundant data that flows out from many application domains. To overcome storage and processing challenges in time series mining, compression techniques are being used. In this paper, we investigate the loss/gain of performance of time series classification approaches when fed with lossy-compressed data. This empirical study is essential for reassuring practitioners, but also for providing more insights on how compression techniques can even be effective in reducing noise in time series data. From a knowledge engineering perspective, we show that time series may be compressed by 90% using discrete wavelet transforms and still achieve remarkable classification accuracy, and that residual details left by popular wavelet compression techniques can sometimes even help achieve higher classification accuracy than the raw time series data, as they better capture essential local features.

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Wavelet transforms and the ECG: a review

Cited by 712 publications

References 113 publications

RAIT: the Rational Approximation and Interpolation Toolbox for Matlab, with Experiments on ECG Signals

RAIT: the Rational Approximation and Interpolation Toolbox for Matlab, with Experiments on ECG Signals

Multiple domain evaluation of watershed hydrology models

Time Series Classification with Discrete Wavelet Transformed Data: Insights from an Empirical Study

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