Singla and Kumar 69 International Journal of Applied Research in Computing, Vol. 2, No. 4, Publication date: 31 October 2014 Abstract - Electrocardiogram (ECG) compression transformation techniques play a vital role in diagnosing various cardiac patients where traditional method fails to detect problem in their Heart’s working. Each cardiac ECG cycle represents various amplitude and intervals under P-QRS-T waves. This compression scheme evaluates amplitude and intervals in ECG signal for analysis. Each P-QRS-T wave represents the electrical activity of the patient. Recently a vast research and techniques have been developed for analyzing the various aspects of ECG signal. Introduced scheme were mostly based upon the Wavelet transformation, Cosine transformation, Fourier transformation and other techniques. All these techniques and algorithms have their pros and cons. Introduced paper enlightens the various techniques and transformation introduced previously for compression of ECG signal. Summation to above this paper also includes a comparative study of various techniques used by researchers for compression of ECG signal. Keywords - Electrocardiogram (ECG) signal, Wireless Sensor Network, Compression techniques, Optimization techniques, Wireless technology. I. INTRODUCTION Exploration of ECG has been abundantly used for diagnosing various chronic cardiac diseases.ECG is an analytical record of magnitude and direction of various electrical activities that in turn are generated by depolarization and re-polarization of pair of atria’s and ventricles present as the core part of patients Heart muscles. Each cardiac cycle also termed as one rhythm of an ECG signal designed as a wave sweeping up the area in a graph with peaks represented as P-QSR-T waves. Sample ECG [1] is shown in Figure 1. Clinically used information precisely based upon the various assets of ECG signal: a) Amplitude of each peak (P, Q, R, S, and T), b) Time of their appearance, c) Time-intervals between peaks. ECG compression system delivers two important aspects as amplitude and time to be exercised during compression. During recent times various compression techniques have been listed that would surely consider above entitled factors. Earlier Introduced methods were based upon the time domain but lacking to take consideration in the frequency domain. ECG is for sure a dominating factor that is responsible for governing and diagnosis of cardiac patients. Time and frequency factors plays vital role in exploring ECG for cardiac diseases. Introduced compression techniques must work to produce results that are acceptable and precise, so that saving and retrieving it anytime will not be an issue. Purpose of compression techniques is to ensure that the integrity of the data instead its bulkiness or amount of bits it contains. Fig. 1 Sample ECG signal representing P-QRS-T waves In Recent years, vast researches have been conducted and came up with new and upgraded versions of algorithms for analyzing and compressing the ECG data. Practical compression [2] is feasible and required as based upon: a) increased storage data, b) feasibility of traversing real ECG. Second factor grasps more concern as it consumes more energy than storing. This paper provides an overlook on various techniques and transformation used for compression of ECG data. Succeeding sections of the paper includes the following- .Section 2 sum up the various related work done so far in the field of compression .Section 3 gives the mutual idea of improvement in the various algorithms and techniques. Section 4 compensates the discussion. ECG Signal Monitored Under Various Compression Techniques and Transmission Environments - A Survey Approach Tony Singla 1 , Rajeev Kumar 2 1 Student, DAV Institute of Engineering and Technology Jalandhar, tony.singla88@gmail.com 2 Assistant Professor (IT Deptt.), DAV Institute of Engineering and Technology Jalandhar, rajeev.daviet@gmail.com