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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Wavelet Signal Processing of Physiologic Waveforms
TL;DR: In this paper, two examples of physiological signal processing using wavelet bases are presented: compression of electrocardiogram (ECG) signals using an Associated Hermite wavelet basis and the removal of artifact from non-invasive blood pressure (NIBP) measurements.
Proceedings ArticleDOI
A Novel Scheme for joint Multi-channel ECG-ultrasound image compression
TL;DR: A novel approach to compress jointly a Multi-Channel Electrocardiogram (MCE) and an ultrasound image and it is shown that this technique allows better performances, in terms of compression ratio (CR) compared to coding separately both modalities.
Journal ArticleDOI
Compression of ECG signal using video codec technology-like scheme
Dihu Chen,Sheng Yang +1 more
TL;DR: In this paper, a method using video codec technology to compress ECG signals was presented, which exploits both intra-beat and inter-beat correlations of the ECG signal to achieve high compression ratios and a low percent root mean square difference (PRD).
Proceedings ArticleDOI
On exploiting interbeat correlation in compressive sensing-based ECG compression
TL;DR: Experimental results show that the proposed method reduces significantly the number of measurements required to achieve good reconstruction quality, validating the potential of using correlation information in compressed sensing-based ECG compression.
Journal ArticleDOI
Lossless electrocardiogram compression technique and gsm based tele-cardiology application
TL;DR: The algorithm has been tested to various ECG data taken from PTB Diagnostic ECG Database and it is observed that the proposed algorithm offers a moderate to high compression ratio.
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.