Real-Time Electrocardiogram (ECG) Signal Analysis and Heart Rate Determination in FPGA Platform

Abstract

Heart disease is one of the leading cause for death of people globally. According to a recent study by the Indian Council of Medical Research (ICMR), about 25 percent of deaths in the age group of 25- 69 years occur because of heart diseases.Electrocardiogram (ECG) is one of the primary tool for the treatment of heart disease. ECG is an important biological signal that reects the electrical activities of the heart. A typical ECG signal consists of mainly ve components namely P,Q, R, S and T wave. Amplitude and morphology of each component contains numerous medical information. The automated detection and delineation of each component in ECG signal is a challenging task in Bio-medical signal processing community. In this research work, a four stage method based on Shannon energy envelope has been proposed in order to detect QRS complex in ECG signal. Peak detection of the proposed algorithm is amplitude threshold free. To evaluate the performance eciency of the proposed method standard MIT-BIH arrhythmia ECG database has been used and get an average accuracy of 99.84 %, Sensitivity 99.95% and Positive Predictivity value 99.88 %. To detect and delineate P and T waves, an algorithm based on Extended Kalman Filter (EKF) with PSO has been proposed. For performance examination, standard QT ECG database has been used. The proposed algorithm yields an average Sensitivity of 99.61 % and Positive Predictivity of 99.00 % for the ECG signal of QT database. A long term automatic heart rate monitoring system is very much essential for standard supervision of a critical stage patient. This work also includes a feld programmable gate array (FPGA) implementation of a system that calculate the heart rate from Electrocardiogram (ECG) signal.