Hamming filter design for ecg signal detection and processing using co-simulation

Abstract

Present work proposes a new method for automatic detection of the QRS complex wave of an ECG signal using digital signal processing (DSP) technique. The main focus in this work is to remove the noises that interfere with the ECG signal. For this purpose, a Hamming window FIR filter is used for the removal of Power line and base line drift noises. Firstly, Noise detection is done using the bit error rate measurement (In bit error rate measurement, two signals of the same type are used, out of which one is containing noisy signal and other is a filtered signal. The value of bit error rate lies between 0 and 1; if value is more close to 1 then presence of noise is maximum). After that Noise filtering is the next step. In filtering of the ECG signal, we have used one band stop filter and one low pass filter. These filters are used to remove 60 Hz power line and 0.5 Hz baseline wander noises. Data has been taken from the MIT/BIH arrhythmias database for the performance analysis of the present design. For the detection of the ECG signal, data is first converted into 16 bit input logical data. Co-simulation technique is used to simulate the Hardware Description Language (HDL) module with Modalism software in real time systems Final step of the present work is the QRS detection. A new method is used to detect the QRS wave which includes the heart rate calculation and R-R time interval. Several analyses performed for the detection of ECG signal verify that Co-simulation is a suitable method to check the HDL module for real time systems.