S. K. Mukhopadhyay, S. Ghosh, S. Chakraborty, S. Das, M. Mitra, S. Mitra
2013 International Journal on Smart Sensing and Intelligent Systems  
Software based efficient lossless Electrocardiogram compression and transmission scheme is proposed here. The algorithm has been tested to various ECG data taken from PTB Diagnostic ECG Database. The compression scheme is such that it outputs only ASCII characters. These characters are transmitted using Global System for Mobile Communication based Short Message Service system and at the receiving end original ECG signal is brought back using the reverse logic of compression. It is observed that
more » ... the proposed algorithm offers a system. Naturally the volume of the data handled would be enormous. Therefore we must need a way to reduce the data storage place without making considerable change in the reconstructed signal and this is exactly the goal of many existing ECG signal compression methods proposed in the literature over the last 4 decades. ECG signal compression techniques can be broadly classified into three major categories: (i) direct data compression, (ii) transformation methods and (iii) parameter extraction techniques. Direct data compression techniques ([3-10]) generally retain samples that contain important information about the signal and discard the rest. Transformation based compression techniques generally detect the redundancies utilizing the spectral and energy distribution analysis. Among transformation schemes, wavelet transformation (WT) [11-15] has become very popular due to the fact that the time-frequency kernel for the WT-based method can better localize the signal components in time-frequency space. Except WT, orthogonal transform [16] and Discrete Cosine Transform [17] have also been used for getting compressed ECG data. Direct and transformation based compression methods are reversible i.e. original signal can be brought back using reverse programming approach. On the other hand parameter extraction methods [18] for compression are irreversible process. These methods are mainly based on linear prediction and long-term prediction methods. In addition to the previous categorization, ECG signal compression schemes can also be classified into lossy and lossless methods. It is obvious that a lossy method can achieve better compression performance but it may lose some important clinical information. On the other hand a lossless method offers a moderate to high compression ratio without jeopardizing the morphology. From juridical and clinical point of view [19, 20] , lossless compression is very much important. Compression of ECG data is essential not only for optimal usage of computer memory but also for increasing the spectral efficiency of communication link for bio-telemetry or tele-cardiology applications. In recent days a huge numbers of mobile telemedicine system design techniques were proposed in the literature [21] [22] [23] [24] [25] [26] [27] [28] [29] [30] [31] [32] [33] [34] [35] . Global System for Mobile Communication (GSM) link was used in [36] to develop an emergency telemonitoring device. Use of Wireless Mesh Networks (WMN) [37] and Code Division Multiple Access (CDMA) network [24] were proposed in telemedicine system. Short Message Service system (SMS) was also used in [38] [39] [40] to transmit compressed ECG
doi:10.21307/ijssis-2017-571 fatcat:2jkckqjy7za5lce3ampae6npom