Paper Title
ACF Algorithm for ECG Signal Implementation

It is believed that the ECG signal is a standard signal for the control of heart rate and diagnose various cardiac problems. In an ECG signal, the most important feature is the QRS complex. The duration of the QRS complex and the height gives a lot of data that allows the doctor to assess the condition of the human heart. However, the ECG signal is noise and other artifacts which hamper the analysis of the signal with bare eyes different algorithms are developed to extract features from the ECG signal. But here we have implemented two algorithms PAN - TOMPKINS and ACF (autocorrelation algorithm) to find the QRS complex of the 12-lead ECG signal. Correlation function is used here to determine whether the ECG signal is normal or abnormal signals are called arrhythmias. MATLAB is used for the simulation of both the algorithms and the same is also implemented in Xilinx FPGAs. This approach provides accurate for the analysis of ECG results in real time. Key Words - Pan Tompkins Algorithm, Autocorrelation Function Algorithm, Band Pass Filter, Differentiator , Moving Window.