ECG QRS Detection for Heart Rate Monitoring (Beats Per Minute Analysis)

In this research paper, D.K. Ravish Bangre explores methodologies for heart rate detection through ECG signal analysis. The study presents an advanced QRS complex detection algorithm capable of accurately identifying heartbeats within one-minute intervals. This research holds significant importance as heart rate monitoring is crucial for maintaining cardiovascular health. The proposed algorithm typically involves digital signal processing techniques such as bandpass filtering to remove noise, derivative-based slope detection for QRS localization, and adaptive thresholding for peak identification. With technological advancements, this methodology can be widely implemented in medical applications using programming frameworks like MATLAB or Python with libraries such as BioSPPy, potentially improving cardiac disease detection in healthcare systems. It is important to note that the intellectual property rights for this specific ECG QRS detection approach belong exclusively to D.K. Ravish Bangre.