Wavelet transforms and the ECG: a review

By Paul S. Addison. Physiological Measurement, 2005

923 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/b2806608d0f6bac17d48ae026cf7b85e3a0beabf

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In Cardiology and Cardiovascular Medicine

In Pulmonary and Respiratory Medicine

Citations in the corpus

Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor Nodes (2011, methodology): “4 wavelet, we herein utilize the orthogonal Daubechies wavelets (db 10) as the most popular wavelet family for ECG compression [16].”
ECG-based heartbeat classification for arrhythmia detection: A survey (2016, methodology): “Besides DWT, continuous wavelet transform (CWT) has also been used to extract features from the ECG signals [99], since it overcomes some of the DWT drawbacks, such as the coarseness of the representation and instability.”
Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis. (2015, positive): “Since then it has been used in a variety of signal processing applications [8,9].”
Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG Via Block Sparse Bayesian Learning (2012, methodology): “Interested readers can refer to [2], [4], and [6] for good surveys on these techniques.”
Arrhythmia recognition and classification using combined linear and nonlinear features of ECG signals (2016, positive): “The DWT filtering and the sub-sampling are given by: ( ) ∑ ( ) ( ) ( ) ( ) ∑ ( ) ( ) ( ) Page 13 of 27 Ac ce pt ed M an us cr ip t 13 A detailed review is provided by Addison (2005).”
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning (2018, methodology): “CWT features have been employed for electrocardiogram analysis [19], electroencephalography [20] and EMG signal analysis, but mainly for lower limbs [21], [22].”
Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review (2019, background): “Addison [62] presented a review of the WT of the ECG signal.”
Wavelet-based Machine Learning Techniques for ECG Signal Analysis (2014, background): “The wavelet basis function [13] is parameterized by the translation ‘b’ and dilation ‘a,’ such basis function is given by, 2) provides a basis for wavelet transformation.”