Journal ArticleDOI
ECG data compression using truncated singular value decomposition
Jyh-Jong Wei,Chuang-Jan Chang,Nai-Kuan Chou,Gwo-Jen Jan +3 more
- Vol. 5, Iss: 4, pp 290-299
TLDR
The results showed that truncated SVD method can provide an efficient coding with high-compression ratios and demonstrated the method as an effective technique for ECG data storage or signals transmission.Abstract:
The method of truncated singular value decomposition (SVD) is proposed for electrocardiogram (ECG) data compression. The signal decomposition capability of SVD is exploited to extract the significant feature components of the ECG by decomposing the ECG into a set of basic patterns with associated scaling factors. The signal information is mostly concentrated within a certain number of singular values with related singular vectors due to the strong interbeat correlation among ECG cycles. Therefore, only the relevant parts of the singular triplets need to be retained as the compressed data for retrieving the original signals. The insignificant overhead can be truncated to eliminate the redundancy of ECG data compression. The Massachusetts Institute of Technology-Beth Israel Hospital arrhythmia database was applied to evaluate the compression performance and recoverability in the retrieved ECG signals. The approximate achievement was presented with an average data rate of 143.2 b/s with a relatively low reconstructed error. These results showed that the truncated SVD method can provide efficient coding with high-compression ratios. The computational efficiency of the SVD method in comparing with other techniques demonstrated the method as an effective technique for ECG data storage or signals transmission.read more
Citations
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Journal ArticleDOI
Classification of Electrocardiogram Signals With Support Vector Machines and Particle Swarm Optimization
Farid Melgani,Yakoub Bazi +1 more
TL;DR: A thorough experimental study to show the superiority of the generalization capability of the support vector machine (SVM) approach in the automatic classification of electrocardiogram (ECG) beats and suggest that further substantial improvements in terms of classification accuracy can be achieved by the proposed PSO-SVM classification system.
Journal ArticleDOI
SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain
Debra McGivney,Eric Y. Pierre,Dan Ma,Yun Jiang,Haris Saybasili,Vikas Gulani,Mark A. Griswold +6 more
TL;DR: By compressing the size of the dictionary in the time domain, this work is able to speed up the pattern recognition algorithm, by a factor of between 3.4-4.8, without sacrificing the high signal-to-noise ratio of the original scheme presented previously.
Journal ArticleDOI
A Real-Time ECG Data Compression and Transmission Algorithm for an e-Health Device
TL;DR: Because the proposed real-time data compression and transmission algorithm can compress and transmit data in real time, it can be served as an optimal biosignal data transmission method for limited bandwidth communication between e-health devices.
Journal ArticleDOI
A wavelet optimization approach for ECG signal classification
TL;DR: A novel approach for generating the wavelet that best represents the ECG beats in terms of discrimina- tion capability is proposed, which makes use of the polyphase representation of the wavelets filter bank and formulates the design problem within a particle swarm optimization (PSO) framework.
Journal ArticleDOI
Automatic defect inspection for LCDs using singular value decomposition
Chi-Jie Lu,Du-Ming Tsai +1 more
TL;DR: In this article, a global image reconstruction scheme using the singular value decomposition (SVD) is proposed to eliminate periodical, repetitive patterns of the textured image, and preserve the anomalies in the restored image.
References
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Journal ArticleDOI
Fetal ECG extraction from single-channel maternal ECG using singular value decomposition
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TL;DR: A new algorithm for ECG signal compression is introduced that can be considered a generalization of the recently published average beat subtraction method, and was found superior at any bit rate.
Journal ArticleDOI
ECG Data Compression Using Fourier Descriptors
TL;DR: The method of Fourier descriptors (FD's) is presented for ECG data compression, resistant to noisy signals and is simple, requiring implementation of forward and inverse FFT.
Journal ArticleDOI
ECG coding by wavelet-based linear prediction
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TL;DR: The significant feature of the proposed technique is that, while the error is nearly uniform throughout the cycle, the diagnostically crucial QRS region is kept free of maximal reconstruction error.
Journal ArticleDOI
Wavelet packet-based compression of single lead ECG
TL;DR: A preliminary investigation of a wavelet packet based algorithm for the compression of single lead ECG is presented, which generates significantly lower data rates with less than one-third the computational effort.