Journal ArticleDOI
ECG data compression techniques-a unified approach
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
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Proceedings ArticleDOI
Low complexity, losless ECG data compression algorthims for Wireless Sensor Network
TL;DR: A significant data reduction has been made for a low data rate wireless communications, i.e. Bluetooth and ZigBee, which helps to reduce the latency and can be implemented by a very low profile microprocessor.
Proceedings ArticleDOI
ECG data compression using wavelet and fractal interpolation
Woo Hee Lee,Young-Ro Yoon +1 more
TL;DR: This paper represents the data compression for ECG signals using the wavelet and adaptive fractal interpolation method and shows a high compression ratio (CR) is achieved with a relatively low percent rms difference (PRD).
Journal Article
ECG Signal Analysis Based on Curvelet Transform and Wiener Filter
Abstract: ----Electrocardiogram (ECG or EKG) is an analytical tool used to assess the electrical activity of the heart over a period of time using electrodes placed on the skin. This paper deals with the analysis of ECG signals using a powerful technique called curvelet transform. The proposed work is carried in two steps, in the first phase, an attempt was made to generate ECG curved forms using MATLAB simulator and in the second phase, the ECG signal was de-noised by removing the corresponding curvelet coefficients at higher scales using curvelet transform. Wiener filter is used to detect the positions of the heart beats. The parameters like the mean difference of the heart beats and the heart rate are computed for ECG signal. Finally, the Statistical results show that our method could significantly improve accuracy, error reduction and has potential to become an effective method for ECG signal analysis.
Journal ArticleDOI
Study on a Low-Complexity ECG Compression Scheme With Two-Tier Sensors
TL;DR: Experimental results show that the proposed scheme method outperforms the conventional ones with respect to ECG reconstruction accuracy at a given bit-rate budget.
Proceedings ArticleDOI
Noise effect on orthogonal transform compression of ECG signals
TL;DR: In this work, LMS algorithm that improves the estimation of classical inner product is analyzed and a selection criteria of the /spl mu/ parameter is obtained in order to outperform inner product performance.
References
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