• Onisha Dua
• Divya Gond
• Sweta Raj
• Dr. Shivani Saxena

The work investigates the efficiency of Finite Impulse Response Kaiser Window and Infinite Impulse Response Butterworth filters in ECG signal processing, which have been used to filter out noise components. For this purpose, numerical simulations of statistical parameters, including signal-to-noise ratio, signal strength, and power retained for both filter designs are measured and compared. This comparison aims to unveil the strengths and limitations of each filter type which is crucial for decision making in clinical research, particularly in detecting subtle abnormalities within the ECG waveforms. MATLAB simulation tool is used to implement these filtering methods on the ECG data collected by the MIT-BIH ECG Arrhythmia database.

Discrete Wavelet Transform, ECG Signal Processing, Finite Impulse Response, MATLAB, Windowing Technique

"A Statistical Comparison of FIR Kaiser Window and IIR Butterworth Filters in ECG Signal Pre-processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.e654-e659, April-2024, Available :http://www.jetir.org/papers/JETIR2404470.pdf

"A Statistical Comparison of FIR Kaiser Window and IIR Butterworth Filters in ECG Signal Pre-processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppe654-e659, April-2024, Available at : http://www.jetir.org/papers/JETIR2404470.pdf