Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

Department of Electrical Engineering

World University root node

Electronics Letters

Effective quality-controlled SPIHT-based ECG coding strategy under noise environments

Noise degrades the rate-distortion performance of any electrocardiogram (ECG) compression algorithm. In distortion driven lossy coding approach, the bit stream is truncated at the bit rate that corresponds to a guaranteed user defined distortion level measured using the percentage root mean square difference (PRD). In many lossy compression methods, noise filtering may be implicitly done when performing the thresholding or/and quantization. In such a case, noise decreases the compression ratio for the specified distortion level. In this paper, we propose an effective wavelet-based lossy compression of noisy ECG signals based on the set partitioning in hierarchical trees (SPIHT) coding algorithm and novel wavelet energy based weighted PRDs (WEWPRD s) criterion. The PRDs measures normalized root mean squared difference between wavelet subband coefficients of the original and compressed signals. The dynamic weights based on wavelet energy feature represent the actual contribution of the subbands that are used to discriminate different frequency subbands, particularly subbands corresponding to noise. The WEWPRDs criterion appears to be a correct representation of the amount of signal distortion at all subbands and robust to insignificant errors in some bands. Thus, this criterion leads to a better measure of the rate-distortion (R-D) performance of the coder. Experiments on several noisy records from the widely used MIT-BIH arrhythmia (mita) database show that the proposed scheme outperforms PRD and wavelet based weighted PRD (WWPRD) measurement criteria based schemes.

TENCON 2008-2008 IEEE Region 10 Conference

An effective wavelet-based lossy compression of noisy ECG signals

A novel and simple quality controlled ECG compression algorithm is proposed using Wavelet energy based diagnostic distortion (WEDD) measure, which localizes the error between the original and the reconstructed signals in the feature space. The compression algorithm is based on Wavelet transform, energy based thresholding and an adaptive quantization scheme. The quality control criterion allows clinically acceptable reconstructions while maintaining high compression ratios. The advantage of the proposed algorithm is that the threshold value and the quantization bits are chosen automatically in few iterations so that the quality of the reconstructed signal is controlled. © 2007 IEEE.

International Conference on Computational Intelligence and Multimedia …

Quality controlled wavelet compression of ECG signals by WEDD

This paper presents a novel phonocardiogram (PCG) signal compression method based on Wavelet transform. The proposed compression method uses energy based thresholding for retaining significant coefficients, uniform scalar zero zone quantizer (USZZQ) for quantizing the amplitudes of the significant coefficients and differencing coder for integer significance map (ISM). This method is tested using the PCG records taken from qdheart and eGeneralMedical databases. The performance of the compression method is assessed in terms of compression ratio (CR), percentage root mean square difference (PRD), Wavelet energy based diagnostic distortion (WEDD) measure and mean opinion score (MOS). The compression method is evaluated with PCG signals of more than 100 records with normal sounds, murmurs, stenosis, noise and other pathologies. High compression ratios with lower distortions are achieved with the proposed method.

IET Digital Library

Wavelet energy based compression of phonocardiogram (PCG) signal for telecardiology

One of the emerging issues in telehealth care system is how effectively the limited and well established mobile technologies that are now almost globally usable are exploited. The main challenge is to develop a mobile telemedicine system to transmit biosignals directly to a specialist in an emergency medical care unit for monitoring/diagnosis using an unmodified mobile telephone which provides the patient's information on the spot without unnecessary delays in seeking care, access to health facility and provision of adequate care at the facility. To provide a practical mobile telemedicine in GSM/GPRS/EDGE/UMTS limited capacity for transmitting the cardiac data for the diagnosis of cardiovascular diseases (CVD) which are widespread health problems with unpredictable and life-threatening consequences in most regions throughout the world, the implementation of biosignals compression technique is focused in this paper. Therefore, a new and simple target data rate (TDR) driven Wavelet-threshold based cardiac signals compression algorithm is presented for mobile telemedicine applications. The performance of the compression system is assessed in terms of compression efficiency, reconstructed signal quality and coding delay. This algorithm is tested using MIT-BIH ECG databases and qdheart PCG database records and the experimental results are compared with other Wavelet based ECG coders. The presented algorithm is less complex because it does not require QRS detection, amplitude and period normalization and period sorting. © 2007 IEEE.

15th International Conference on Advanced Computing and Communications …

Wavelet-based ECG and PCG signals compression technique for mobile telemedicine

In this paper, a novel Wavelet Energy based diagnostic distortion (WEDD) measure is proposed to assess the reconstructed signal quality for ECG compression algorithms. WEDD is evaluated from the Wavelet coefficients of the original and the reconstructed ECG signals. For each ECG segment, a Wavelet energy weight vector is computed via five-level biorthogonal discrete Wavelet transform (DWT). WEDD is defined as the sum of Wavelet energy weighted percentage root mean square difference of each subband. The effectiveness of this measure is validated by linear (linear polynomial and cubic polynomial) and nonlinear (logistic) regression analysis between the computed WEDD values and the mean opinion score (MOS) given by cardiologists. WEDD provides a better prediction accuracy and exhibits a statistically better monotonic relationship with the MOS ratings than Wavelet based weighted percentage root mean square difference (PRD) measure (WWPRD), PRD and other objective measures. Standard correlation coefficient and Spearman rank-order correlation coefficient (SROCC) between the WEDD/MOS ratings is 0.969 and 0.9624, respectively. © 2007 Elsevier Ltd. All rights reserved.

Biomedical Signal Processing and Control

Wavelet energy based diagnostic distortion measure for ECG

A new threshold based Wavelet ECG data compression method is proposed. The proposed method uses linear phase Biorthogonal 9/7 discrete Wavelet transform. Wavelet coefficients are selected based on energy packing efficiency of each subband. Significant wavelet coefficients are quantized with uniform scalar zero zone quantizer (USZZQ). Significance map is created to store the indices of the significant coefficients and this map is encoded efficiently with less number of bits by applying Huffman coding on the differences between the indices. ECG records from the MIT-BIH arrhythmia and compression test database are selected as test data. For the record 117, the proposed method achieves a compression ratio of 17.641:1 with lower percentage root mean square difference (PRD) compared to other threshold based methods. An average compression ratio of 20.8231:1 with an average PRD of 7.1641% is achieved for 19 records. The performance is better compared to the SPIHT and ASEC method for some selected records. © 2006 IEEE.

2006 Annual IEEE India Conference

Wavelet based ECG compression with large zero zone quantizer

In this paper, a new Wavelet threshold based ECG signal compression technique using uniform scalar zero zone quantizer (USZZQ) and Huffman coding on differencing significance map (DSM) is proposed. Wavelet coefficients are selected based on the energy packing efficiency of each sub-band. Significant Wavelet coefficients are quantized with uniform scalar zero zone quantizer. Significance map is created to store the indices of the significant coefficients. This map is encoded efficiently with less number of bits by applying Huffman coding on the differences between indices in the significance map. ECG records from the MIT-BIH arrhythmia database are selected as test data. For the record 117, the proposed technique achieves a compression ratio of 18.7:1 with lower percentage root mean square difference (PRD) compared to other threshold based methods. The proposed technique is tested for MIT-BIH arrhythmia record 119 and a compression ratio of 21.81:1 is achieved with a PRD value of 3.716% which is much lower compared to the reported PRD value of 5.0 and 5.5% of set partitioning in hierarchical tress (SPIHT) and analysis by synthesis ECG compressor (ASEC), respectively. The noise eliminating capability of the proposed technique is also demonstrated in this work. The proposed technique achieves the required compression ratio with less reconstruction error for GSM-based cellular telemedicine system. © 2007 Elsevier Ltd. All rights reserved.

Wavelet threshold based ECG compression using USZZQ and Huffman coding of DSM

A new novel Wavelet-threshold based ECG signal compression method is proposed using linear phase Biorthogonal 917 discrete Wavelet transform, uniform scalar zero zone quantizer (USZZQ) and Huffman coding of the difference between two consecutive index of the significant coefficients. The compression performance of the proposed method is better compared to EZW SPIHT ASEC and other wavelet-threshold based coders. The proposed method is tested for the MIT-BIH arrhythmia record 119 and a compression ratio of 21.8:1 is achieved with PRD value of 3.7166\% which is much lower as compared to the reported PRD value of 5.0\% and 5.5\% of SPIHT and ASEC, respectively. The proposed method requires less computation time since it does not need QRS detection, period normalization, amplitude normalization and mean removal. Hence, the proposed method can be used for the transmission of ECG signal over the band limited telephone networks.

2006 Fourth International Conference on Intelligent Sensing and Information …

Wavelet-threshold based ECG compression with smooth retrieved quality for telecardiology

This paper presents a novel ECG data compression algorithm based on discrete sinc interpolation (DSI) technique. The compression and decompression of ECG data is achieved using discrete sinc interpolation (DSI), which is realized by an efficient discrete fourier transform (DFT). The proposed algorithm is evaluated using MIT-BIH Arrhythmia Database (sampled at 360Hz with 11 bits resolution). The performance of the proposed DSI based algorithm is compared with the performance of the widely used ECG data compression algorithms such as AZTEC, FAN, Hilton and Djohan algorithms. It is observed that higher compression ratio (CR) is achieved with a relatively lower Percentage RMS Difference (PRD) by DSI algorithm. The diagnostic distortion is measured in terms of average absolute error (AAE), which is lower in case of the DSI algorithm compared to the AZTEC and FAN algorithm. © 2005 IEEE.