R - Peak Detection using Altered Pan-Tompkins Algorithm

Abstract

Electrocardiogram (ECG) evaluation is performed by signal processing in majority of the systems. Accurate QRS (r-peak) detection is a vital step for analyzing variations in heart rate. Algorithms based on the differentiated ECG signals can be computed efficiently and are useful for real-time analysis. The data from the MIT database consists of time-domain data of the electric potentials from the heart. In this work the data is processed and analyzed to detect and diagnose cardiac problems. ECG wave is used to detect and diagnose abnormalities in blood pressure, blood cholesterol and blood sugar. Variations in ECG is used in stress analysis and emotional activity. This modified Pan- Tompkins algorithm used in our work achieved a sensitivity of 94.54%.