Performance evaluation of ECG compression techniques

ECG data compression algorithm for tele-monitoring of cardiac patients

Abstract: This paper reports an efficient electrocardiogram (ECG) data compression algorithm for tele-monitoring of cardiac patients from rural area, based on combination of two encoding techniques with discrete cosine transform. The proposed technique provides good compression ratio (CR) with low percent root-mean-square difference (PRD) values. For performance evaluation of the proposed algorithm 48 records of ECG signals are taken from MIT-BIH arrhythmia database. Each record of ECG signal is of duration 1 minute and sampled at sampling frequency of 360 Hz. Noise of the ECG signal has been removed using Savitzky-Golay filter. To transform the signal from time domain to frequency domain, discrete cosine transform has been used which compacts energy of the signal to lower order of frequency coefficients. After normalisation and rounding of transform coefficients, signals are encoded using dual encoding technique which consists of run length encoding and Huffman encoding. The dual encoding technique compresses data significantly without any loss of information. The proposed algorithm offers average values of CR, PRD, quality score, percent root mean square difference normalised, RMS error and SNR of 11.49, 3.43, 3.82, 5.51, 0.012 and 60.11 dB respectively.

Study of various data compression techniques used in lossless compression of ECG signals

Abstract: As we know that developments in technology are introducing various methods for Tele-cardiology. Tele-cardiology includes many of the applications and this is one of the fields in telemedicine which have seen excellent growth. In the procedures of Tele-cardiology we record a extremely large amount of ECG real time data. Therefore we require an efficient and lossless technique that is able to perform compression of recorded ECG signals. In this paper we have studied and analyzed various lossless data compression techniques used in the compression of ECG signals. In the course of studying various techniques we have presented the analysis of some most widely used time domain techniques those are AZTEC (Amplitude zone time epoch coding) technique and Turning point technique (TP) and in transformation based compression techniques we have presented the study of Discrete Cosine Transform technique (DCT) performed with Huffman coding technique and Empirical Mode Decomposition (EMD) technique. The overall performance of all these techniques are studied and analyzed on the basis of two main parameters those are the compression ratio (CR) and Percent Root means square Difference (PRD). We have used the data base of physionet.org website for the calculation of CR and PRD. We have calculated and compared the CR and PRD values using all above discussed techniques for 28 sets of the recorded data.

Study and analysis of ECG compression algorithms

Abstract: Electrocardiogram (ECG) is one testing method for measuring electrical activity of heart. ECG is the graphical representation of the electrical signal generated from heart. Heart is an organ of human which pump blood for the entire body. It require huge amount of data to store and transmit these ECG signals. So it is necessary for compression of the ECG signals. In few last years, many algorithms have evolved to compress the ECG signals, in that four algorithms such as Amplitude Zone Time Epoch Coding algorithm (AZTEC), Turning Point (TP), compression by using Discrete Cosine Transform (DCT) and Backward difference and compression by using Empirical Mode Decomposition (EMD) are implemented and explained detail. The performance of all the algorithms are analyzed by using two parameters namely, Percent Root means square Difference (PRD) and Compression Ratio (CR). The CR and PRD are calculated for all 48 ECG records from the database of MIT-BIH arrhythmia. Finally the CR and PRD values are compared with all the four algorithms. The experimental result indicates that the compression by EMD gives better CR and PRD compare to all other methods.

The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

Abstract: A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...

A Method for the Construction of Minimum-Redundancy Codes

Abstract: An optimum method of coding an ensemble of messages consisting of a finite number of members is developed. A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.

Discrete Cosine Transform

Abstract: A discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed. It is shown that the discrete cosine transform can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering. Its performance is compared with that of a class of orthogonal transforms and is found to compare closely to that of the Karhunen-Loeve transform, which is known to be optimal. The performances of the Karhunen-Loeve and discrete cosine transforms are also found to compare closely with respect to the rate-distortion criterion.

A method for the construction of minimum-redundancy codes

Abstract: An optimum method of coding an ensemble of messages consisting of a finite number of members is developed. A minimum-redundancy code is one constructed in such a way that the average number of coding digits per message is minimized.

Discrete Cosine Transform: Algorithms, Advantages, Applications

Abstract: Discrete Cosine Transform. Definitions and General Properties. DCT and Its Relations to the Karhunen-Loeve Transform. Fast Algorithms for DCT-II. Two Dimensional DCT Algorithms. Performance of the DCT. Applications of the DCT. Appendices. References. Index.