Abstract— ECG signals are the heart wave signals used to identify the heart disease. This kind of signal processing requires effective signal feature extraction as well as integration with real environment. The presented work is defined to provide the solution to both these problems. The feature detection is here been defined in the form of QRS detection. The implementation of work is done in Android environment. To perform the QRS detection, < Final Year Projects > a traditional Pam Tompkins algorithm is defined. This algorithmic approach is here defined with the specification of series of filters. These filters are able to remove the signal level impurities as well as to obtain the signal features. Based on these features QRS detection over the signal will be performed. Once these features are extracted, the integration of this model is done in android environment to represent it as real time application. In android environment, the model will accept stored signal and will identify the QRS over the signal under defined approach. The work is implemented in matlab and android integrated environment.
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