G. Srinivasan

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Changes in the normal rhythm of a human heart may result in different cardiac arrhythmias, which may be immediately causes irreparable damage to the heart sustained over long periods of time. The ability to automatically identify arrhythmias from ECG recordings is important for clinical diagnosis and treatment. In this paper we proposed an Artificial Neural(More)
— Automatic electrocardiogram (ECG) signal classification plays a significant role in the clinical applications, to overcome the problems occur during manual annotation of the ECG recordings. The ECG beat morphologies and disease states cannot be defined easily by a single representation, since it can vary greatly for each person. This paper proposes ECG(More)
  • Gn Srinivasan, Prathibha Rk, Raunak Kasera, Assistant Professor
  • 2014
A proper framework of the requirement engineering process is very important for the success of this project. All the stages in requirement engineering must be complete and they must blend into each other to form a fruitful model. This model establishes the basic structure with the help of which all the software requirement processes can be handled,(More)