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

Abstract

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.