Journal ArticleDOI
Adaptive filter for event-related bioelectric signals using an impulse correlated reference input: comparison with signal averaging techniques
TLDR
In this paper, an adaptive impulse correlated filter (AICF) was proposed to estimate the deterministic component of the signal and remove the noise uncorrelated with the stimulus even if this noise is colored, as in the case of evoked potentials.Citations
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Journal ArticleDOI
A Nonlinear Bayesian Filtering Framework for ECG Denoising
TL;DR: A nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings, demonstrating superior results compared with conventional ECG denoising approaches such as bandpass filtering, adaptive filtering, and waveletDenoising, over a wide range of ECG SNRs.
Journal ArticleDOI
Principal component analysis in ECG signal processing
TL;DR: Several ECG applications are reviewed where PCA techniques have been successfully employed, including data compression, ST-T segment analysis for the detection of myocardial ischemia and abnormalities in ventricular repolarization, extraction of atrial fibrillatory waves for detailed characterization of atrium fibrillation, and analysis of body surface potential maps.
Journal ArticleDOI
ECG Denoising and Compression Using a Modified Extended Kalman Filter Structure
TL;DR: Efficient denoising and lossy compression schemes for electrocardiogram (ECG) signals based on a modified extended Kalman filter (EKF) structure are presented, suitable for a hybrid system that integrates these algorithmic approaches for clean ECG data storage or transmission scenarios with high output SNRs, high CRs, and low distortions.
Journal ArticleDOI
Application of independent component analysis in removing artefacts from the electrocardiogram
TL;DR: An ICA algorithm is tested on three-channel ECG recordings taken from human subjects, mostly in the coronary care unit, and results are presented that show that ICA can detect and remove a variety of noise and artefact sources in these ECGs.
Journal ArticleDOI
Removing artifacts from electrocardiographic signals using independent components analysis
TL;DR: This work uses a new tool called independent component analysis (ICA) that blindly separates mixed statistically independent signals, even if both overlap in frequency, and proposes a self-adaptive step-size, derived from the study of the averaged behavior of those parameters, and a two-layers neural network.
References
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Book
Adaptive Signal Processing
Bernard Widrow,Samuel D. Stearns +1 more
TL;DR: This chapter discusses Adaptive Arrays and Adaptive Beamforming, as well as other Adaptive Algorithms and Structures, and discusses the Z-Transform in Adaptive Signal Processing.
Journal ArticleDOI
Adaptive noise cancelling: Principles and applications
Bernard Widrow,J.R. Glover,John M. McCool,J. Kaunitz,C.S. Williams,R.H. Hearn,James R. Zeidler,Jr. Eugene Dong,R.C. Goodlin +8 more
TL;DR: It is shown that in treating periodic interference the adaptive noise canceller acts as a notch filter with narrow bandwidth, infinite null, and the capability of tracking the exact frequency of the interference; in this case the canceller behaves as a linear, time-invariant system, with the adaptive filter converging on a dynamic rather than a static solution.
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
Convergence analysis of LMS filters with uncorrelated Gaussian data
Arie Feuer,E. Weinstein +1 more
TL;DR: It is found that the adaptive coefficient μ, which controls the rate of convergence of the algorithm, must be restricted to an interval significantly smaller than the domain commonly stated in the literature.
Journal ArticleDOI
Adaptive Fourier estimation of time-varying evoked potentials
C. A. Vaz,Nitish V. Thakor +1 more
TL;DR: In this estimation procedure the evoked response is modeled as a dynamic Fourier series and the Fourier coefficients are estimated adaptively by the least-mean-square algorithm.