Different Approaches for Biomedical Signal (ECG) Compression in Secure Communication Network

Storage and transmission limitations have made biomedical signal data compression an important feature for most biomedical computerized systems. In addition, when compressed biomedical signals (ECG) or data are delivered over a public channel such as the Internet, TV etc their privacy and security would also be an important issue. Electrocardiogram (ECG) signal is a very important measure to know the Heart actual conditions so that easily found deceases. Various techniques have been proposed over the years for addressing the problem. In our paper, we are analyzing different approaches of biomedical signal compression such as ECG signal in secure communication network.ECG signals are collected both over long periods of time and at high resolution from patients. This creates substantial volumes of data for storage and transmission. Data compression seeks to reduce the number of bits of information required to store or transmit digitized ECG signals without significant loss of signal quality. A wide range of compression techniques based on different transformation techniques like MSVQ, genetic optimization, SPARSE 2D SEPARABLE TRANSFORM. DST and DCT were evaluated to find an optimal compression strategy for ECG data compression. All Testing was performed on artificially signals from the standard CSE and MIT-BIH database.