Journal ArticleDOI
Wavelet and wavelet packet compression of electrocardiograms
TLDR
Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECGs are clinically useful.Abstract:
Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data. Pilot data from a blind evaluation of compressed ECG's by cardiologists suggest that the clinically useful information present in original ECG signals is preserved by 8:1 compression, and in most cases 16:1 compressed ECG's are clinically useful.read more
Citations
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Book ChapterDOI
Fully parameterized Discrete Wavelet Packet Transform architecture oriented to FPGA
TL;DR: A fully parameterized Discrete Wavelet Packet Transform (DWPT) architecture based on a folded Distributed Arithmetic implementation, which makes possible to design any kind of wavelet bases.
Journal ArticleDOI
Pre-processing deconvolution based technique for improving the performances of ECG codecs: Comparison to SPIHT
TL;DR: A deconvolution preprocessing module for ECG codec performance improvement (DPM-ECPI) is presented and it is shown that this new compression scheme is particularly interesting than a direct coding.
Proceedings ArticleDOI
Optimum Wavelet Transform-Based ECG Compressionand Dissimilarity Measureson Noise Performance Analysis
Mustafa Namdar,Lutfiye Durak +1 more
TL;DR: In this article, an optimum wavelet transform-based ECG compression technique is proposed and its noise performance analysis is investigated, which guarantees an error limit as small as possible measured by the percent root mean square difference (PRD) for the reconstructed ECG signal at every segment while keeping the compression ratio (CR) as large as possible with reasonable implementation complexity.
Generation And Reconstruction Of Eeg Signals Using Matlab
TL;DR: A novel scheme for signal compression based on the discrete wavelet packet transform (DWPT) decomposition was proposed and the mother wavelet and the basis of wavelet packets were optimized and the wavelet coefficients were encoded with a modified version of the embedded Zero tree algorithm.
Energy Awareness in Mobile Wellness Applications
TL;DR: This study investigates techniques that focus on reducing energy consumption in mobile wellness monitoring applications by dividing the monitoring system into three levels and exploring the energy saving methods at each level.
References
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Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI
Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Journal ArticleDOI
Orthonormal bases of compactly supported wavelets
TL;DR: This work construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity, by reviewing the concept of multiresolution analysis as well as several algorithms in vision decomposition and reconstruction.
Journal ArticleDOI
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
Amir Said,William A. Pearlman +1 more
TL;DR: The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods.