Matlab Signal Processing Project- Atrial Fibrillation Compresively Electrocardiogram- ClickMyProject
An electrocardiogram (ECG) is an important diagnostic tool for the assessment of several diseases. In this process, we implement the a machine learning based Random forest framework, which is previously trained on a general signal data set is transferred to carry out automatic ECG diagnostics by classifying patient ECG’s into corresponding cardiac conditions. The Main focus of this process is to implement a simple, reliable and easily applicable machine learning technique for the classification of the selected signals from the dataset. The results demonstrated that the transferred deep learning classification cascaded with a conventional back propagation neural network were able to obtain very high performance rates.
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