scispace - formally typeset
Journal ArticleDOI

ECG data compression techniques-a unified approach

Reads0
Chats0
TLDR
The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods and a framework for evaluation and comparison of ECG compression schemes is presented.
Abstract
Electrocardiogram (ECG) compression techniques are compared, and a unified view of these techniques is established. ECG data compression schemes are presented in two major groups: direct data compression and transformation methods. The direct data compression techniques are ECG differential pulse code modulation (DPCM) and entropy coding, AZTEC, Turning-point, CORTES, Fan and SAPA algorithms, peak-picking, and cycle-to-cycle compression methods. The transformation methods include Fourier, Walsh, and Karhunen-Loeve transforms. The theoretical bases behind the direct ECG data compression schemes are presented and classified into three categories: tolerance-comparison compression, DPCM, and entropy coding methods. A framework for evaluation and comparison of ECG compression schemes is presented. >

read more

Citations
More filters
Proceedings ArticleDOI

Clinical quality guaranteed physiological data compression in mobile health monitoring

TL;DR: This paper proposes a simple method called "Critical Markers" method that is based on detection of peaks and valleys in the original signal that maintains high compression performance while also guaranteeing high clinical quality.
Proceedings ArticleDOI

Transform-based reduction of inter-channel correlation applied to lossless coding of multichannel ECG

TL;DR: This work discusses the practical aspect of the transform-based decorrelation of simultaneously recorded ECG channels and finds that the statistical properties featured by uncorrelated signals in the transform domain are more appropriate for various data distribution-based coding techniques (Huffman).
Journal ArticleDOI

Multichannel Data Compression using Wavelet Subbands Arranging Technique

TL;DR: The proposed WSAT technique is an appropriate approach to simultaneously compress multichannel data with significant low compressed data rate at low error and is recommended by the American Heart Association for routine visual readings of compressed and reconstructed ECG signals.
Proceedings ArticleDOI

The Combining Kernel Principal Component Analysis with Support Vector Machines for Time Series Prediction Model

TL;DR: The novel time series analysis model integrates the advantage of wavelet, PSO, KPCA and SVM to create a model that has greater generality ability and higher accuracy.
Journal ArticleDOI

A quality-on-demand electrocardiogram signal compression using modified set partitioning in hierarchical tree

TL;DR: This paper focuses on the implementation of electrocardiogram signal compression using wavelet-based progressive coding such as set partitioning in hierarchical tree and its modified version to achieve improvement in the speed at low bit rate.
References
More filters
Journal ArticleDOI

A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Journal ArticleDOI

A Method for the Construction of Minimum-Redundancy Codes

TL;DR: A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.
Journal ArticleDOI

Linear prediction: A tutorial review

TL;DR: This paper gives an exposition of linear prediction in the analysis of discrete signals as a linear combination of its past values and present and past values of a hypothetical input to a system whose output is the given signal.
Journal ArticleDOI

Arithmetic coding for data compression

TL;DR: The state of the art in data compression is arithmetic coding, not the better-known Huffman method, which gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.
Proceedings ArticleDOI

Orthogonal transforms for digital signal processing

TL;DR: The utility and effectiveness of these transforms are evaluated in terms of some standard performance criteria such as computational complexity, variance distribution, mean-square error, correlated rms error, rate distortion, data compression, classification error, and digital hardware realization.
Related Papers (5)