International Journal of Biomedical Engineering and Technology
In this paper, an improved method for electrocardiogram (ECG) signal compression using Set Partit... more In this paper, an improved method for electrocardiogram (ECG) signal compression using Set Partitioning in Hierarchical Trees (SPIHT) algorithm is proposed. ECG signals are compressed based on different transform such as discrete cosine transform and discrete wavelet transform with modified SPIHT. The modified SPIHT algorithm yields good compression with controlled quantity of signal degradation and requires computational time as compared to earlier published SPIHT algorithms. The proposed algorithm is suitable for the ECG signal compression for telemedicine or e-health system due to minimum computational time.
In this paper, a method proposed for the HTTP compression of one dimensional (1-D) nonstationary ... more In this paper, a method proposed for the HTTP compression of one dimensional (1-D) nonstationary nature of signal like speech and electrocardiogram signal. Here compression is achieved based on discrete wavelet transform decompositions at different levels (DWT) and run-length encoding (RLE). For the HTTP all process is done based on text analysis of wavelet coefficient, its prevent the signal information from unauthorized users. The performance of compression is analyzed by compression ratio (CR) and other fidelity parameters like signal-to-noise ratio (SNR) are shows the compressed/reconstructed signal properties.
Wavelet based electrocardiogram compression at different quantization levels
Communications in Computer and Information Science, 2011
... Expert Systems with Applications 37(8), 57515757 (2010) 5. Manikandan, MS, Dandapat, S.: Wav... more ... Expert Systems with Applications 37(8), 57515757 (2010) 5. Manikandan, MS, Dandapat, S.: Wavelet threshold based TDL and TDR algorithms for real ... Computer Methods and Programs in Biomedicine 9(4), 109117 (2009) 7. Saritha, C., Sukanya, V., Murthy, YN: ECG Signal ...
Communications in Computer and Information Science, 2011
In this paper, a transform based methodology is presented for compression of electrocardiogram (E... more In this paper, a transform based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT). A comparative study of performance of different transforms for ECG signal is made in terms of Compression ratio (CR), Percent root mean square difference (PRD), Mean square error (MSE), Maximum error (ME) and Signal-to-noise ratio (SNR). The simulation results included illustrate the effectiveness of these transforms in biomedical signal processing. When compared, Discrete Cosine Transform and Fast Fourier Transform give better compression ratio, while Discrete Wavelet Transform yields good fidelity parameters with comparable compression ratio.
Journal of Mathematical Modelling and Algorithms, 2012
In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG... more In this paper, a wavelet based methodology is presented for compression of electrocardiogram (ECG) signal. The methodology employs new wavelet filters whose coefficients are derived with beta function and its derivatives. A comparative study of performance of different existing wavelet filters and the Beta wavelet filters is made in terms of compression ratio (CR), percent root mean square difference (PRD), mean square error (MSE) and signal-to-noise ratio (SNR). When compared, the Beta wavelet filters give better compression ratio and also yields good fidelity parameters as compared to other wavelet filters. The simulation result included in this paper shows the clearly increased efficacy and performance in the field of biomedical signal processing.
2012 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2012, 2012
In this paper, a speech enhancement technique proposed by Soon and Koh is examined and improved b... more In this paper, a speech enhancement technique proposed by Soon and Koh is examined and improved by exploiting different window functions for pre-processing of speech signals. In this method, instead of using twodimensional (2-D) Discrete Fourier Transform, Discrete Wavelet Transform is employed with a hybrid wiener filter based on one-dimensional (1-D) wiener filter and 2-D Wiener filter. A comparative study of performance of different window functions such as Blackman, Cosh and Exponential windows has been made in terms of Signal to Noise Ratio (SNR), Maximum Error (ME), and Mean Square Error (MSE). When compared, Cosh window gives the best performance than all other known window functions.
In this paper, optimized wavelet filters for speech compression are proposed whose wavelet filter... more In this paper, optimized wavelet filters for speech compression are proposed whose wavelet filter coefficients are derived with different window techniques such as Kaiser and Blackman windows via simple linear optimization. When the developed wavelet filters are exploited for speech compression, they not only give better compression ratio but also yield good fidelity parameters as compared to other wavelet filters. A comparative study of performance of different existing wavelet filters and the proposed wavelet filters is made in terms of compression ratio (CR), signal-tonoise ratio (SNR), peak signal-to-noise ratio (PSNR) and normalized root-mean square error (NRMSE) at different thresholding levels. The simulation result included in this paper shows increased efficacy and improved performance of the proposed filters in the field of speech signal processing.
In this paper, an ECG compression method based on beta wavelet using lossless encoding technique ... more In this paper, an ECG compression method based on beta wavelet using lossless encoding technique is presented. Wavelet based compression techniques minimize the compression distortion, while run-length encoding (RLE) further increases the compression without any loss of relevant signal information. The developed technique employs a modified thresholding. The wavelet filters based on beta function and its derivative, improves the compression of signal as compared to earlier existing thresholding technique. The simulation results clearly show the superiority of this technique in terms of compression ratio and a desirable signal quality. For performance evaluation, several significant parameters such as percent root mean square difference (PRD), signal-to-noise ratio (SNR) and compression ratio (CR) are used, whereas signal quality and its relevant information are evaluated by QRS peak detection.
2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE), 2013
In this paper, a ECG compression system is presented based on two-dimensional discrete wavelet tr... more 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.
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Papers by Ranjeet Kumar