Compression Performance Analysis of Electrogastrogram (Egg) Using Different Wavelet Transforms For Telemedicine

2021 ◽  
Vol 23 (05) ◽  
pp. 286-293
Author(s):  
Gokul M ◽  
◽  
Jothiraj S ◽  
Pradeep Murugesan ◽  
Monisha R ◽  
...  
Keyword(s):  
Compression Ratio ◽  
Wavelet Transforms ◽  
Graphical Representation ◽  
Transmission Rate ◽  
Signal Compression ◽  
Signal Loss ◽  
Compression Performance ◽  
Non Invasive ◽  
Egg Signal ◽  
Mean Square Difference

Electrogastrogram (EGG) is the non-invasive graphical representation of stomach’s electrical activity for diagnosing stomach Disorders. EGG signal compression has an important role in Tele-diagnosis, Tele-prognosis and survival analysis of all stomach dysrhythmias, when the patient is geographically isolated. There are plenty of signal compression techniques available and proposed over years. Due to some drawbacks like high cost, signal loss and poor compression ratio leads the signal into inefficient at receiver’s end. The compression of digital EGG in telemedicine holds three major advantages like efficient & economic usage of storage data, reduction of the data transmission rate and good transmission bandwidth conversation. In this study EGG signals are tested with different wavelet transforms such as Biorthogonal, coiflet, Daubechies, Haar, reverse biorthogonal and symlet wavelet transforms using MATLAB software, in order to find best performance wavelet for telemedicine. The performance is mathematically analyzed using the values of Percent Root Mean Square Difference (PRD), Compression ratio (CR) and recovery ratio. The result of better compression performance in signal compression could definitely be a great asset in telemedicine field for transferring more quantities of Biological signals.

Improving Energy Efficiency and Throughput in Heterogeneous Mobile Ad Hoc Networks

2011 ◽  
pp. 37-49
Author(s):  
Manu J. Pillai ◽  
M. P. Sebastian
Keyword(s):  
Ad Hoc ◽  
Transmission Rate ◽  
Mac Protocol ◽  
Signal Loss ◽  
High Data ◽  
Communication Links ◽  
Adhoc Networks ◽  
Simulation Results ◽  
Demand Routing ◽  
Hoc Networks

The nodes are expected to transmit at different power levels in heterogeneous mobile adhoc networks, thus leading to communication links of different length. Conventional MAC protocols that unconditionally presume that links are bi-directional and with unvarying energy distribution may not succeed or execute badly under such circumstances. Interference and signal loss resulting out of distance and fading diminish the entire throughput attained in heterogeneous networks to a greater extent. This article presents a MAC protocol, which adaptively transmits data frames using either the energy efficient nodes or a list of high data rate assistant nodes. In addition, a cross-layer based energy level on-demand routing protocol that adaptively regulates the transmission rate on basis of congestion is projected as well. Simulation results illustrate that the proposed protocols considerably diminish energy consumption and delay, and attain high throughput in contrast with the Hybrid MAC and traditional IEEE 802.11 protocols

scholarly journals An Enhanced Run-Length Encoding Compression Method for Telemetry Data

2017 ◽  
Vol 24 (3) ◽  
pp. 551-562 ◽  
Author(s):  
Yanhu Shan ◽  
Yongfeng Ren ◽  
Guoyong Zhen ◽  
Kaiqun Wang
Keyword(s):  
Compression Ratio ◽  
High Capacity ◽  
Acquisition System ◽  
Compression Method ◽  
Telemetry Data ◽  
Vibration Signals ◽  
Run Length ◽  
Compression Performance ◽  
Error Factor ◽  
Method Show

AbstractThe telemetry data are essential in evaluating the performance of aircraft and diagnosing its failures. This work combines the oversampling technology with the run-length encoding compression algorithm with an error factor to further enhance the compression performance of telemetry data in a multichannel acquisition system. Compression of telemetry data is carried out with the use of FPGAs. In the experiments there are used pulse signals and vibration signals. The proposed method is compared with two existing methods. The experimental results indicate that the compression ratio, precision, and distortion degree of the telemetry data are improved significantly compared with those obtained by the existing methods. The implementation and measurement of the proposed telemetry data compression method show its effectiveness when used in a high-precision high-capacity multichannel acquisition system.

Multi-Channel ECG Signals Compression Algorithm Using Simultaneous Orthogonal Matching Pursuit

2012 ◽  
Vol 457-458 ◽  
pp. 1305-1309
Author(s):  
Yong Ting Li ◽  
Xiao Yan Chen ◽  
Yue Wen Liu
Keyword(s):  
Signal Processing ◽  
Compression Ratio ◽  
Matching Pursuit ◽  
Orthogonal Matching Pursuit ◽  
Compression Method ◽  
Petersburg Institute ◽  
Redundant Dictionary ◽  
Compression Performance ◽  
Ecg Signals ◽  
Ecg Compression

Sparse decompression is a new theory for signal processing, having the advantage in that the base (dictionary) used in this theory is over-complete, and can reflect the nature of signa1. So the sparse decompression of signal can get sparse representation, which is very important in data compression. In this paper, a novel ECG compression method for multi-channel ECG signals was introduced based on the Simultaneous Orthogonal Matching Pursuit (S-OMP). The proposed method decomposes multi-channel ECG signals simultaneously into different linear expansions of the same atoms that are selected from a redundant dictionary, which is constructed by Hermite fuctions and Gobar functions in order to the best match the characteristic of the ECG waveform. Compression performance has been tested using a subset of multi-channel ECG records from the St.-Petersburg Institute of Cardiological Technics database, the results demonstrate that much less atoms are selected to present signals and the compression ratio of Multi-channel ECG can achieve better performance in comparison to Simultaneous Matching Pursuit (SMP).

scholarly journals Performance Comparison of Hartley Transform with Hartley Wavelet and Hybrid Hartley Wavelet Transforms for Image Data Compression

2014 ◽  
Vol 12 (6) ◽  
pp. 3634-3641
Author(s):  
Prachi Natu ◽  
H.B. Kekre ◽  
Tanuja Sarode
Keyword(s):  
Wavelet Transform ◽  
Compression Ratio ◽  
Wavelet Transforms ◽  
Image Data ◽  
Performance Comparison ◽  
Local Component ◽  
Hartley Transform ◽  
Acceptable Quality ◽  
Hartley Transforms ◽  
Image Data Compression

This paper proposes image compression using Hybrid Hartley wavelet transform. The paper compares the results of Hybrid Hartley wavelet transform with that of orthogonal Hartley transform and Hartley Wavelet Transform. Hartley wavelet is generated from Hartley transform and Hybrid Hartley wavelet is generated from Hartley transform combined with other orthogonal transform which contributes to local features of an image. RMSE values are calculated by varying local component transform in hybrid Hartley wavelet transform and changing the size of it. Sizes of local component transform is varied as N=8, 16, 32, 64. Experiments are performed on twenty sample color images of size 256x256x3. Performance of Hartley Transform, Hartley Wavelet transform and Hybrid Hartley wavelet Transform is compared in terms of compression ratio and bit rate. Performance of Hartley wavelet is 35 to 37% better than that of Hartley transform whereas performance of hybrid Hartley wavelet is still improved than Hartley wavelet transform by 15 to 20%. Hartley-DCT pair gives best results among all Hybrid Hartley Transforms. Using hybrid wavelet maximum compression ratio up to 32 is obtained with acceptable quality of reconstructed image.

Radar signal compression using wavelet transforms

2001 ◽  
Author(s):  
Yan Zhou ◽  
Fei-peng Li ◽  
Yu Xu ◽  
Qian-qing Qin ◽  
Deren Li
Keyword(s):  
Wavelet Transforms ◽  
Radar Signal ◽  
Signal Compression

scholarly journals A Study on Wavelet Transform Using Image Analysis

2018 ◽  
Vol 7 (2.32) ◽  
pp. 94 ◽  
Author(s):  
CMAK. Zeelan Basha ◽  
K M. Sricharan ◽  
Ch Krishna Dheeraj ◽  
R Ramya Sri
Keyword(s):  
Image Analysis ◽  
Wavelet Transform ◽  
Wavelet Transforms ◽  
Haar Wavelet ◽  
Matlab Simulation ◽  
Haar Wavelet Transform ◽  
Compression Performance ◽  
Analysis Technique ◽  
Energy Retention ◽  
And Performance

The wavelet transforms have been in use for variety of applications. It is widely being used in signal analysis and image analysis. There have been lot of wavelet transforms for compression, decomposition and reconstruction of images. Out of many transforms Haar wavelet transform is the most computationally feasible wavelet transform to implement. The wave analysis technique has an understandable impact on the removal of noise within the signal. The paper outlines the principles and performance of wavelets in image analysis. Compression performance and decomposition of images into different layers have been discussed in this paper. We used  Haar distinct wavelet remodel (HDWT) to compress the image. Simulation of wavelet transform was done in MATLAB. Simulation results are conferred for the compression with Haar rippling with totally different level of decomposition. Energy retention and PSNR values are calculated for the wavelets. Result conjointly reveals that the extent of decomposition will increase beholding of the photographs goes on decreasing however the extent of compression is incredibly high. Experimental results demonstrate the effectiveness of the Haar wavelet transform in energy retention in comparison to other wavelet transforms. 

Compression ratio boundaries for predictive signal compression

2001 ◽  
Vol 10 (2) ◽  
pp. 323-326 ◽  
Author(s):  
O.S. Pianykh ◽  
J.M. Tyler
Keyword(s):  
Compression Ratio ◽  
Signal Compression
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