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Denoising cyclostationary framework for enhanced electrocardiogram analysis

Gupta, C.N., Palaniappan, Ramaswamy (2009) Denoising cyclostationary framework for enhanced electrocardiogram analysis. In: 2007 Computers in Cardiology. . pp. 93-96. ISBN 978-1-4244-2533-4. (doi:10.1109/CIC.2007.4745429) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/CIC.2007.4745429

Abstract

We present a novel two module scheme for efficient analysis of noisy Electrocardiogram (ECG) signals. The first module consists of a segmentation algorithm which uses cyclostationary analysis for the detection of a single heart beat or cycle (P wave-QRS complex-T wave). The time domain cyclostationary (CS) algorithm exploits the statistical properties of the recorded periodic ECG signal and does not use any prior knowledge about signal morphology. Using the obtained cycle length the next module uses repeated applications of Principal Component Analysis (PCA) to reduce multiple additive noises from the multi trial and multi channel recorded ECG signals. PCA has been used for noise reduction in ECG but the method of repeated applications of PCA is novel. In this study, PCA was applied in 2 stages. In the first stage, PCA was applied to multi-channel ECG signals from one trial. The output ECG signals from the first stage were used in the second stage, where PCA was applied to multi-trial ECG signals from a single channel. The proposed scheme was tested with the 12-lead ECG signals from PTB Diagnostic database (National Metrology Institute of Germany) provided on physionet website which showed significant improvement in Signal to Noise ratio. We suggest that this simple scheme can be used for automatic analysis of noisy ECG signals where the extraction and denoising of single heart beat provide enhanced physiological features which enables better clinical interpretation of cardiovascular functionalities.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/CIC.2007.4745429
Additional information: Unmapped bibliographic data: C7 - 4745429 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - Comput Cardiol [Field not mapped to EPrints] AD - Department of Computing and Electronic Systems, University of Essex, Colchester, United Kingdom [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] C3 - Computers in Cardiology [Field not mapped to EPrints]
Uncontrolled keywords: Automatic analysis, Cycle lengths, Cyclostationary, Cyclostationary analysis, De-noising, Diagnostic database, ECG signals, Efficient analysis, Electrocardiogram analysis, Electrocardiogram signals, Germany, Heart beats, Multi channels, National metrology institutes, Noise reductions, P waves, Physiological features, PhysioNet, Principal components, Prior knowledge, QRS complexes, Repeated applications, Segmentation algorithms, Signal-to-noise ratios, Single channels, Statistical properties, T waves, Time domains, Web sites, Cardiology, Electrocardiography, Feature extraction, Metal recovery, Principal component analysis, Signal processing, Signal to noise ratio, Timing jitter, Electrochromic devices
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 14:04 UTC
Last Modified: 30 May 2019 08:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70722 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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