ECG Compression Using Ensemble Polynomial Modeling: Comparison with the Wavelet-Based Technique

The proposed ECG compression technique combined two approaches, ECG beat alignment and the polynomial modelling. QRS complexes are first detected then aligned in order to reduce high frequency changes from beat to beat. These changes are modelled by means of a polynomial projection. ECGs from MIT-BIH database are used to evaluate the performance of the proposed technique. A comparison with the DCT approach is performed by means CR/PRD curves.

[1]  K.M. Buckley,et al.  ECG data compression using cut and align beats approach and 2-D transforms , 1999, IEEE Transactions on Biomedical Engineering.

[2]  H. Koymen,et al.  Multichannel ECG data compression by multirate signal processing and transform domain coding techniques , 1993, IEEE Transactions on Biomedical Engineering.

[3]  José García,et al.  ECG signal compression plus noise filtering with truncated orthogonal expansions , 1999, Signal Process..

[4]  K. Hynynen,et al.  Arrays of multielement ultrasound applicators for interstitial hyperthermia , 1999, IEEE Transactions on Biomedical Engineering.

[5]  Shankar M. Krishnan,et al.  A dynamic nonlinear time domain model for reconstruction and compression of cardiovascular signals with application to telemedicine , 2003, Comput. Biol. Medicine.

[6]  Marta Karczewicz,et al.  ECG data compression by spline approximation , 1997, Signal Process..

[7]  W. Philips,et al.  ECG data compression with time-warped polynomials , 1993, IEEE Transactions on Biomedical Engineering.

[8]  Arnon D. Cohen,et al.  ECG signal compression using analysis by synthesis coding , 2000, IEEE Transactions on Biomedical Engineering.

[9]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

[10]  Robert S. H. Istepanian,et al.  Optimal zonal wavelet-based ECG data compression for a mobile telecardiology system , 2000, IEEE Transactions on Information Technology in Biomedicine.

[11]  M. Abo-Zahhad,et al.  A new hybrid algorithm for ECG signal compression based on the wavelet transformation of the linearly predicted error. , 2001, Medical engineering & physics.

[12]  Hayrettin Koymen,et al.  Compression of digital biomedical signals , 2006 .

[13]  L. Batista,et al.  Compression of ECG signals by optimized quantization of discrete cosine transform coefficients. , 2001, Medical engineering & physics.

[14]  Mohammed Abo-Zahhad,et al.  An effective coding technique for the compression of one-dimensional signals using wavelet transforms. , 2002, Medical engineering & physics.

[15]  Ioan Tabus,et al.  Using contexts and R-R interval estimation in lossless ECG compression , 2002, Comput. Methods Programs Biomed..

[16]  J. Kozumplík,et al.  Wavelet transform in electrocardiography--data compression. , 1997, International journal of medical informatics.

[17]  A Koski,et al.  Lossless ECG encoding. , 1997, Computer methods and programs in biomedicine.

[18]  W. A. Coberly,et al.  ECG data compression techniques-a unified approach , 1990, IEEE Transactions on Biomedical Engineering.

[19]  S. Ahmed,et al.  ECG data compression using optimal non-orthogonal wavelet transform. , 2000, Medical engineering & physics.