In this paper, a ECG compression system is presented based on two-dimensional discrete wavelet transform (2D DWT) and Huffman coding technique. In this method, two different approaches are utilized to construct a 2D array of 1D ECG signal using cut and align (CAB) technique, therefore ECG 2D array is decomposed with 2D DWT which results more number of insignificant coefficients. They are considered as zero amplitude value which accelerate compression rate and Huffman coding maintains the signal quality due to its lossless nature of compression. The average compression performance of algorithm is 65% with 0.999 correlation score.

An efficient compression system for ECG signal using QRS periods and CAB technique based on 2D DWT and Huffman coding

Cardiac Disease has become very common perhaps because of increasingly busy lifestyles. The rapid advancement of mobile communication technologies offers innumerable opportunities for the development of software and hardware applications for remote monitoring of chronic disease. This paper describes a remote health-monitoring service that provides an end-to-end solution. We present an efficient data mining-based solution that recognizes different CVDs (such as ventricular flutter/fibrillation, atrial fibrillation, atrial premature beat, premature ventricular contraction) from the compressed ECG, it was proposed to perform real-time classification of Cardiac Vascular Disease (CVD) based on data mining techniques. The subset of the features selection from the compressed ECG was performed using the Genetic algorithm and the clustering was performed using Expectation Maximization.

A Remote Healthcare Monitoring System for Faster Identification of Cardiac Abnormalities from Compressed ECG Using Advanced Data Mining Approach

This article analyses the performance of: (i) linear transform: Slantlet transform (SLT), (ii) nonlinear transform: lifting wavelet transform (LWT) and (iii) nonlinear transform (LWT) with normalisation for electrocardiogram (ECG) compression. First, an ECG signal is transformed using linear transform and nonlinear transform. The transformed coefficients (TC) are then thresholded using bisection algorithm in order to match the predefined user-specified percentage root mean square difference (UPRD) within the tolerance. Then, the binary look up table is made to store the position map for zero and nonzero coefficients (NZCs). The NZCs are quantised by Max–Lloyd quantiser followed by Arithmetic coding. The look up table is encoded by Huffman coding. The results show that the LWT gives the best result as compared to SLT evaluated in this article. This transform is then considered to evaluate the effect of normalisation before thresholding. In case of normalisation, the TC is normalised by dividing the TC by (...

ECG compression using Slantlet and lifting wavelet transform with and without normalisation

This paper explores the new algorithm for ECG signal compression based on Joint-multiresolution analysis (J-MRA) using Gaussian pyramid and wavelet analysis. From signal compression prospective, MRA play key role to present signal in few numbers of coefficients with its parental features. The proposed algorithm has been tested on 10 second length of 19 ECG signals from MIT-BIH Arrhythmia database and compared with recent contemporary techniques. The simulation results show that the proposed method achieves high compression ratio at relatively low distortion in comparison with other methods. Analysis contains various simulation results, where the average compression is 86.14% at 4.96% of PRD and correlation founded between original and reconstructed signal is 0.998. It can clearly demonstrate the algorithm efficiency towards to save a great amount of storage space, bandwidth and power consumption especially in data transmission for tele-health care or m-health care systems.

ECG signal compression algorithm based on joint-multiresolution analysis (J-MRA)

An Electrocardiogram (ECG) signal compression becomes more area of interest due to increases demand of tel-e-healthcare system. In this manuscript, dual tree discrete wavelet decomposition (DT-DWT) based ECG signal compression is exploited using zero run-length coding techniques. The main advancement of proposed technique, its sensitivity of generating sparse data set that helps to enhance compression performance of system. Performance of method evaluated through compression ratio and percentage root-mean square difference and quality evaluated using the cross correlation between the original and reconstructed MIT-BIH records. As discuses in results, proposed method is good as compare to earlier developed techniques in term of compression.

Dual tree DWT analysis based electrocardiogram signal compression using zero coding technique

inter-frame correlations, video codec technology can be used for ECG compression. For ECG signals, there In this paper, we present a method using is a little difference, so some pre-process will be video codec technology to compress ECG needed: ECG signals should be segmented and period signals. This method exploits both intra-beat normalized to a sequence of beat cycles with the and inter-beat correlations of the ECG sig- same size. Then these beat cycles can be treated as nals to achieve high compression ratios (CR) 'picture frames' and compressed with a video codec. and a low percent root mean square differ- In this work, we present a method using video ence (PRD). Since ECG signals have both codec technology to compress ECG signals. This intra-beat and inter-beat redundancies like method exploits both intra-beat and inter-beat correvideo signals, which have both intra-frame lations of the ECG signals to achieve high compresand inter-frame correlation, video codec tech- sion ratios (CR) and a low percent root mean square nology can be used for ECG compression. In difference (PRD). Although video codec technology order to do this, some pre-process will be was developed to compress video signals, it can be needed. The ECG signals should firstly be used to compress other signals as well, and we illussegmented and normalized to a sequence of trate how video codec technology can be used to combeat cycles with the same length, and then press ECG signals. In Section II, we take a brief overthese beat cycles can be treated as picture view of video codec technology. Section III presents frames and compressed with video codec the coding algorithm. Experimental results and comtechnology. We have used records from MIT- parisons with other algorithm are presented in SecBIH arrhythmia database to evaluate our algo- tion IV. At last, we provide conclusions. rithm. Results show that, besides compression efficiently, this algorithm has the advantages of resolution adjustable, random 2. OVERVIEW OF VIDEO CODEC TECHaccess and flexibility for irregular period and NOLOGY QRS false detection. Representing video material in a digital form requires a large number of bits. The volume of data generated by digitizing a video signal is too large for most storage and transmission systems. This means that compression is essential for most digital video applications. Statistical analysis of video signals indi

Sheng Yang

Papers

Compression of ECG signal using video codec technology-like scheme Compression of ECG signal using video codec technology-like scheme