Journal ArticleDOI
Data processing of stress ECGs using discrete cosine transform
TLDR
Application of the discrete cosine transform to noisy records has resulted in near perfect reproduction of the original noise free ECG without significant alterations in its morphological features.About:
This article is published in Computers in Biology and Medicine.The article was published on 1998-11-01. It has received 19 citations till now. The article focuses on the topics: Wiener filter & Discrete cosine transform.read more
Citations
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Journal ArticleDOI
ECG signal denoising and baseline wander correction based on the empirical mode decomposition
TL;DR: A new ECG enhancement method based on the recently developed empirical mode decomposition (EMD) that is able to remove both high-frequency noise and BW with minimum signal distortion and is validated through experiments on the MIT-BIH databases.
Journal ArticleDOI
ECG Analysis Using Multiple Instance Learning for Myocardial Infarction Detection
TL;DR: The rationale for applying multiple instance learning (MIL) to automated ECG classification is discussed and a new MIL strategy called latent topic MIL is proposed, by which ECGs are mapped into a topic space defined by a number of topics identified over all the unlabeled training heartbeats and support vector machine is directly applied to the ECG-level topic vectors.
Journal ArticleDOI
Gaussian Noise Filtering from ECG by Wiener Filter and Ensemble Empirical Mode Decomposition
Kang-Ming Chang,Shing-Hong Liu +1 more
TL;DR: Experimental result showed that EEMD had better noise-filtering performance than EMD and FIR Wiener filter, based on the mode-mixing reduction between near IMF scales.
Proceedings ArticleDOI
ECG denoising based on the empirical mode decomposition.
TL;DR: A new ECG denoising method based on the recently developed Empirical Mode Decomposition (EMD) is proposed, able to remove high frequency noise with minimum signal distortion.
Journal ArticleDOI
A comprehensive performance analysis of EEMD-BLMS and DWT-NN hybrid algorithms for ECG denoising
TL;DR: A thorough analysis of the performance of two hybrid signal processing schemes for denoising ECG signals, compared to the conventional EMD, C-EEMD, EEMD-LMS as well as the DWT thresholding (DWT-Th) based methods through extensive simulation studies.
References
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Journal ArticleDOI
A Real-Time QRS Detection Algorithm
Jiapu Pan,Willis J. Tompkins +1 more
TL;DR: A real-time algorithm that reliably recognizes QRS complexes based upon digital analyses of slope, amplitude, and width of ECG signals and automatically adjusts thresholds and parameters periodically to adapt to such ECG changes as QRS morphology and heart rate.
Proceedings ArticleDOI
Orthogonal transforms for digital signal processing
K. R. Rao,N. U. Ahmed +1 more
TL;DR: The utility and effectiveness of these transforms are evaluated in terms of some standard performance criteria such as computational complexity, variance distribution, mean-square error, correlated rms error, rate distortion, data compression, classification error, and digital hardware realization.
Journal ArticleDOI
Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection
Nitish V. Thakor,Y.-S. Zhu +1 more
TL;DR: Several adaptive filter structures are proposed for noise cancellation and arrhythmia detection and an adaptive recurrent filter structure is proposed for acquiring the impulse response of the normal QRS complex.
Journal ArticleDOI
Removal of Base-Line Wander and Power-Line Interference from the ECG by an Efficient FIR Filter with a Reduced Number of Taps
J. A. van Alsté,T. S. Schilder +1 more
TL;DR: Linear phase filtering is proposed for the removal of baseline wander and power-line frequency components in electrocardiograms with a considerably reduced number of impulse response coefficients.
Journal ArticleDOI
Subspace-based signal analysis using singular value decomposition
TL;DR: A unified approach is presented to the related problems of recovering signal parameters from noisy observations and identifying linear system model parameters from observed input/output signals, both using singular value decomposition (SVD) techniques.
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Removing artifacts from electrocardiographic signals using independent components analysis
Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection
Nitish V. Thakor,Y.-S. Zhu +1 more