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Cardiovascular disease has the highest mortality rate globally which mean that more people die annually from it than from any other cause. The disease should be detected and anticipated as early as possible because of its fatality. For many years, electrocardiograph (ECG) has become the golden standard for cardiovascular disease detection. The main purpose of this research work is to develop ECG signal interpretation software on Android 2.2 platform. The methods consist of ECG data preparation, QRS detector, heart rate and QRS time extraction, and classification. The system classifies the abnormalities of heart rhythm into: Premature Ventricular Contraction (PVC) and Supra Ventricular Tachycardia (SVT). To manifest the performance of this software, data from MIT-BIH Arrhythmia Database were used. The overall accuracy of this software in determining heart rate is 97.10%. This software also has average N-Accuracy of 99.15%, average V-Accuracy of 84.22%, average SVT-Accuracy of 97.78%, and the overall classification accuracy of 93.71%.