Vector Quantization of ECG
نویسنده
چکیده
|An improved wavelet compression algorithm for ECG signals has been developed with the use of vector quantization on wavelet coeecients. Vector quantization on scales of long duration and low dynamic range retains feature integrity of the ECG with a very low bit-per-sample rate. Preliminary results indicate that the proposed method excels over standard techniques for high delity compression .
منابع مشابه
A 2-D ECG compression algorithm based on wavelet transform and vector quantization
In this paper, we proposed a new two-dimensional (2-D) wavelet-based electrocardiogram (ECG) data compression algorithm. A 1-D ECG data is first segmented and aligned to a 2-D data array, thus the two kinds of correlation of heartbeat signals can be fully utilized. And then 2-D wavelet transform is applied to the constructed 2-D ECG data array. A modified vector quantization (VQ) is employed to...
متن کاملElectrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification
Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classifi...
متن کاملAn Ecg Signal Compressor Based on Optimized Quantization of Discrete Cosine Transform Co- Efficients
This paper presents an ECG compressor based on optimized quantization of discrete cosine transform (DCT) coefficients. The ECG is partitioned in blocks and each DCT block is quantized using a quantization vector and a threshold vector. These vectors are defined for each signal so that the entropy is minimized for a target distortion or, alternatively, the distortion is minimized for a target en...
متن کاملHidden Markov Models in Wavelet Analysis
The paper deals with a mathematical model using a structure designed for an application of pattern recognition in ECG signals. The overall process of recognition is consist of generation of a code book, vector quantization, Markov model learning, and recognition. A Hidden Markov Model (HMM) structure with vector–valued observation sequences can be used for the characterization of cardiac arryth...
متن کاملCombination of Different Classifiers for Cardiac Arrhythmia Recognition
This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG sig...
متن کامل