Informatics Publishing Limited

Amit Awasthi ¹, Neetesh Nema ², Manish Mahant ³

Affiliations
1 Department of CSE, RKDF Engineering College, Bhopal (M.P.), IN
2 Department of CSE, SRIT Engineering College, Jabalpur (M.P.), IN
3 Department of CSE, SRGI Engineering College, Jabalpur (M.P.), IN

Abstract

Storm Prediction Center Severe Weather (SVRGIS) Geographic Information System (GIS) applications are becoming increasingly popular in many organizations, including the federal government. Emergency operations have taken advantage of these capabilities. “GIS can be beneficial in many ways, but in the simplest of terms, it connects people to information through geography. Government can use GIS to store, manage, and access information about its facilities, people, and environment. It gives government officials a way to visualize data that helps them make decisions about project planning and economic development.

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Amit Awasthi ¹, Niresh Sharma ¹

Affiliations
1 Dept. of Computer Science Engineering, RKDF Engineering College, Bhopal, IN

Abstract

This research work is supervised by ANN based algorithm to classify the ECG wave forms. The ECG waveform gives the almost all information about activity of the heart, which is depending on the electrical activity of the heart. In this paper we are focused only five features of ECG signal P, Q, R, S, T. This is achieved by extracting the various features and duration of ECG waveform P-wave, PR segment, PR interval, QRS Complex, ST segment, T-wave, ST- interval, QTc and QRS voltage. ECG signal and heart rate are used the parameter for detection diseases, most of the data comes from PhysioDataNet and MIT-BIH data base. This research is focused on to find out best neural network structure which classifies the abnormalities of heart diseases. This technique also identifies the normal region for classification of abnormalities; because of ECG waveform is varying from person to person at different condition.

Keywords

ECG, ANN, PhysioDataNet, Classification.

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