Bio-signals are essentially nonstationary signals; they display a fractal like self-similarity. The bio-potentials generated by the muscles of the heart results in a signal called electro cardiogram (ECG). It is one of the most important physiological parameter, which is being extensively used for knowing the state of cardiac patients. They may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at
random – in the time scale. However, to study and pinpoint anomalies in voluminous data collected over several hours is strenuous and time consuming. Therefore, computer based analytical tools for in-depth study and classification of data over daylong intervals can be very useful in diagnostics.
This paper emphasis on analysis & interpretation of the ECG by using Artificial Neural
Network (ANN). ECG analysis using ANN is an important tool in which two or more successive ECG recordings from the same patients are compared in order to find changes due to disorders
in cardiac. Reliable detection of the QRS complex in either a normal or an abnormal ECG and its analysis is the first and foremost task in almost every ECG signal analysis system aimed at
the diagnostic interpretation of ECG.
This paper explains briefly, hardware required to pick up ECG signal. ECG is digitized and given to the neural network as input. Neural network is designed and training & testing sets are prepared in such away that it analyses ECG and gives output as normal or abnormal ECG. The result indicate ANN, if properly trained and validated will be a useful aid in the attempt to improve the diagnosis yield of the ECG. This study has shown large evidence in favour of using neural nets to improve the exercise ECG as a non-invasive
technique for detecting heart diseases.
Click here to download
random – in the time scale. However, to study and pinpoint anomalies in voluminous data collected over several hours is strenuous and time consuming. Therefore, computer based analytical tools for in-depth study and classification of data over daylong intervals can be very useful in diagnostics.
This paper emphasis on analysis & interpretation of the ECG by using Artificial Neural
Network (ANN). ECG analysis using ANN is an important tool in which two or more successive ECG recordings from the same patients are compared in order to find changes due to disorders
in cardiac. Reliable detection of the QRS complex in either a normal or an abnormal ECG and its analysis is the first and foremost task in almost every ECG signal analysis system aimed at
the diagnostic interpretation of ECG.
This paper explains briefly, hardware required to pick up ECG signal. ECG is digitized and given to the neural network as input. Neural network is designed and training & testing sets are prepared in such away that it analyses ECG and gives output as normal or abnormal ECG. The result indicate ANN, if properly trained and validated will be a useful aid in the attempt to improve the diagnosis yield of the ECG. This study has shown large evidence in favour of using neural nets to improve the exercise ECG as a non-invasive
technique for detecting heart diseases.
Click here to download
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