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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Journal ArticleDOI
Self-Detection and Self-Diagnosis Methods for Sensors in Intelligent Integrated Sensing System
TL;DR: In this paper, the authors proposed a self-diagnosis system for smart sensors to find out the cause or type of the error when failure occurs, which can also perform real-time fault-tolerant conveniently.
Proceedings ArticleDOI
Efficient thresholding-based ECG compressors for high quality applications using cosine modulated filter banks
TL;DR: Two compression schemes that include nearly perfect reconstruction cosine modulated filter banks for the signal decomposition are proposed and are evaluated for highly reliable applications, where the reconstructed signal must be very similar to the original.
Journal ArticleDOI
FPGA compression of ECG signals by using modified convolution scheme of the Discrete Wavelet Transform
TL;DR: FPGA design of ECG compression by using the Discrete Wavelet Transform (DWT) and one lossless encoding method and a model is developed for a fixed-point convolution scheme which has a good performance in relation to the throughput, the latency, the maximum frequency of operation and the quality of the compressed signal.
Journal ArticleDOI
On-line resolution of overlapping chromatograms using the wavelet transform
Xueguang Shao,Shuquan Hou +1 more
Proceedings ArticleDOI
Wireless personal health ECG monitoring application
TL;DR: This article proposes a framework which will collect readings from ECG monitoring devices in a wireless network, then compress the collected data and automatically send this data to the physician through the patient's handheld device like 'smart' phone and an efficient compression algorithm for compressing the ECG waveforms in real time into a form that can be easily transmitted from the handheld device using SMS.
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.