This ground-breaking study introduces a unique method for integrating an Arduino Uno and PYNQ Z2 board to continuously monitor electrocardiogram (ECG) and heart rate variability. The system easily integrates an ECG sensor (AD8232) and uses webcam analysis to do non-invasive Remote Photo-plethysmography (RPPG). Heart rate data is precisely retrieved by examining the green light emission from the subject's face. By using 2nd order bandpass IIR filters to the processing of ECG data from the Arduino, precise signal extraction is made possible. Advanced algorithms are used for additional analysis, notably in identifying R-peaks and deriving insightful information about the subject's heartbeats. The individual's health status is accurately assessed using statistical and machine learning approaches in conjunction with thorough feature extraction. The system enables real-time monitoring of heart rate variability, eliminating theneed for intrusive wired connections and ensuring a seamless user experience.