De-noising of ECG signal using FIR filter and QRS detection

Abstract

Electrocardiogram (ECG) machines are usually used for medical diagnosis of heart activities of human body now days. Every portion of ECG is very essential for the diagnosis of different cardiac problems. But the amplitude and duration of ECG signal is usually corrupted by different types of noise and interference based on interfaces between ECG machines and human body. It can change the real amplitude and duration of the signal. In electrocardiogram (ECG), noise removal and QRS complex play the vital role for detecting various heart diseases. So, noise free and accurate QRS detection becomes very important in ECG signal. In this thesis we proposed new algorithms which are able to make it noise free and detect QRS complex in ECG signal. Generally, a noise free algorithm removes the noisy signal and we have used Remez exchange algorithm for 1st algorithm, designed an arbitrary magnitude with FIR filter for 2nd algorithm, FIR filter with window method for 3rd proposed algorithm, We have also proposed moving average filter and moving average weighted window, and an algorithm based on forward difference quotient and threshold for corresponding algorithms respectively for noise elimination of ECG. QRS complex of noise free ECG signal have been detected by proposed detection algorithm. The performance parameters are SNR, MSE and Correlation and accuracy, sensitivity, specificity, precision are used to justify the proposed noise free algorithm and QRS detection. The real data examples and experimental results approve new algorithms and prove the robustness of the algorithms which are more effective in ECG applications.