POWER EFFICIENT PROCESSOR FOR PREDICTING VENTRICULAR ARRHYTHMIA BASED ON ECG

Electronics and Communication Engineering

The power efficient processor for predicting ventricular arrhythmia based on ECG is a fully integrated signal processor for predicting arrhythmia. The term “arrhythmia” refers to any change from the normal sequence of electrical impulses. This paper presents the design of signal processor (ESP) for the prediction of ventricular arrhythmia using a unique set of ECG features. Real-time and adaptive techniques for the detection and the delineation of the P-QRS-T waves were investigated to extract the fiducial points. The proposed architecture of this paper analysis the logic size, area and power consumption using Xilinx. The P-QRS-T detection is done using MATLAB. In MATLAB, Pat and Tompkins algorithm is used for removing powerline noise, muscular noise and base line noise. After removal of these noises using MATLAB the signal is forced manually in Model Sim. The filtering is done using Model Sim. After filtration, the signal is again sent into MATLAB for arrhythmia classification. The objective of this project is find and increases the number of interval as compared to the previous work, and increase the possibility of the Predicting Ventricular Arrhythmia and also to reduce the power consumption and area. The results obtained are in such a manner that the area is reduced and throughput is increased.

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