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
The singular value decomposition—applied in the modelling and prediction of quasiperiodic processes
P.P. Kanjilal,Sarbani Palit +1 more
TL;DR: In this paper, singular value decomposition is used as a tool in the analysis of quasiperiodic processes, where the prime orthogonal components are used to separate the regular and the irregular parts of the process.
Journal ArticleDOI
Reduced-size neural networks through singular value decomposition and subset selection
TL;DR: The Letter proposes an application of SVD and subset selection for optimising the size of feedforward neural networks; the Mackey Glass (MG) series is used as an example.
Journal ArticleDOI
Constrained ECG compression using best adapted wavelet packet bases
TL;DR: A study of ECG compression using an upper bound on the percentage root mean square difference (PRD) is presented, which could be specified by the clinician after correlating the quality of the compressed versions of the ECG and the resulting PRD.