Data Compression of ECG Signals using Error Back Propagation (EBP) Algorithm
Anuradha Pathak1, A. K. Wadhwani2
1Anuradha Pathak , Student M.E (2nd year), Measurement and Control systems, Electrical Engineering Department, MITS , Gwalior, Madhya Pradesh, India.
2Dr. A.K Wadhwani, Professor Electrical Engineering Department, MITS, Gwalior, Madhya Pradesh, India.
Manuscript received on March 02, 2012. | Revised Manuscript received on March 31, 2012. | Manuscript published on April 30, 2012. | PP: 256-260 | Volume-1 Issue-4, April 2012 | Retrieval Number: D0349041412/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Heart is one of the vital parts of our human body, which maintains life line. The paper deals with an efficient composite method which has been developed for data compression and signal reconstruct of ECG signals. ECG data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. After carrying out detailed studies and by training different topologies of error back propagation (EBP) artificial neural network (ANN) with respect to variation in number of hidden layers and number of elements, the topology with single hidden layer and four elements in each hidden layer has been finalized for ECG data compression using a Physionet.org data base. The compression ratio (CR) in ANN method increases with increase in number of ECG cycles. The entire programming in this paper is carried out on the version of MATLAB 7.8.
Keywords: Compression, Data compression, ECG, Compression ratio (CR), PRD and EBP.