Proper monitoring of heart rate is important in the early diagnosis, the continued evaluation of patients, and the creation of wearable health care systems. Nevertheless, records of ECGs that are obtained on low-power portable devices are susceptible to motion artifact, baseline drift, muscle noise, and electromagnetic interference, leading to a considerable decrease in the reliability of measurements. This paper introduces a heart rate sensor based on noise-resilient noise cancellation algorithms for the ECG sensor, utilizing both hardware and digital noise cancellation methods. This system uses a high-gain instrumentation amplifier with a customized circuit to eliminate common-mode interference, which is then followed by analog bandpass filtering to eliminate baseline wander and high-frequency noise. The digitized signals are then further processed with an optimized digital pipeline, which consists of a 0.5-40 Hz bandpass filter. Experimental findings from the measured conditions of control in lab experiments and simulated motion conditions demonstrated that the proposed method is significantly more effective in terms of signal-to-noise ratio and reduces erroneous detections, providing more reliable and steady heart rate estimation. The suggested system shows high potential for application in low-cost wearable health-monitoring systems, remote patient-care technologies, and smart e-textile implementations where reliable physiological sensing is needed.