Journal ArticleDOI
Multichannel ECG Data Compression Based on Multiscale Principal Component Analysis
Laxmi Sharma,Samarendra Dandapat,Anil Mahanta +2 more
- Vol. 16, Iss: 4, pp 730-736
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TLDR
Multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression and the lowest mean opinion score error value of 5.56% is found.Abstract:
In this paper, multiscale principal component analysis (MSPCA) is proposed for multichannel electrocardiogram (MECG) data compression. In wavelet domain, principal components analysis (PCA) of multiscale multivariate matrices of multichannel signals helps reduce dimension and remove redundant information present in signals. The selection of principal components (PCs) is based on average fractional energy contribution of eigenvalue in a data matrix. Multichannel compression is implemented using uniform quantizer and entropy coding of PCA coefficients. The compressed signal quality is evaluated quantitatively using percentage root mean square difference (PRD), and wavelet energy-based diagnostic distortion (WEDD) measures. Using dataset from CSE multilead measurement library, multichannel compression ratio of 5.98:1 is found with PRD value 2.09% and the lowest WEDD value of 4.19%. Based on, gold standard subjective quality measure, the lowest mean opinion score error value of 5.56% is found.read more
Citations
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Multiscale Energy and Eigenspace Approach to Detection and Localization of Myocardial Infarction
TL;DR: The results show that the proposed MEES approach can successfully detect the MI pathologies and help localize different types of MIs.
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Detection of Shockable Ventricular Arrhythmia using Variational Mode Decomposition
TL;DR: This paper proposes a new method for detection and classification of shockable ventricular arrhythmia (VT/VF) and non-shockable Ventricular arrHythmia episodes from Electrocardiogram (ECG) signal and results reveal that the feature subset derived from mutual information based scoring and the RF classifier produces accuracy, sensitivity and specificity values.
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Heart monitoring systems—A review
TL;DR: This paper introduces the heart monitoring system in five modules: body sensors, signal conditioning, analog to digital converter and compression, wireless transmission, and analysis and classification, and introduces the function of the module, recent developments, and their limitation and challenges.
Journal ArticleDOI
Multilead ECG data compression using SVD in multiresolution domain
TL;DR: A new thresholding technique based on multiscale root fractional energy contribution is proposed, which selects the singular values depending on the clinical importance of the wavelet subbands in multiresolution domain.
Journal ArticleDOI
Hybrid method based on singular value decomposition and embedded zero tree wavelet technique for ECG signal compression
TL;DR: The proposed algorithm is efficient and flexible with different types of ECG signal for compression, and controls quality of reconstruction, and can play a big role to save the memory space of health data centres as well as save the bandwidth in telemedicine based healthcare systems.
References
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Book
Introduction to data compression
TL;DR: The author explains the development of the Huffman Coding Algorithm and some of the techniques used in its implementation, as well as some of its applications, including Image Compression, which is based on the JBIG standard.
Journal ArticleDOI
Quantization
Robert M. Gray,David L. Neuhoff +1 more
TL;DR: The key to a successful quantization is the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.
Journal ArticleDOI
Multiscale PCA with application to multivariate statistical process monitoring
TL;DR: Multiscale Principal Component Analysis (MSPCA) as mentioned in this paper combines the ability of PCA to decorrelate the variables by extracting a linear relationship with that of wavelet analysis to extract deterministic features and approximately decorrelation of autocorrelated measurements.
Journal ArticleDOI
The weighted diagnostic distortion (WDD) measure for ECG signal compression
TL;DR: The correlation between the proposed WDD measure and the MOS test measure (MOS/sub error/) was found superior to the correlation betweenThe popular PRD measure andThe MOS/ sub error/.
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.