Energy-Efficient PPG Processor Design for Reliable Estimation of Heart Rate and Biometric Authentication

Wearable technology is rapidly transforming the landscape of personal health monitoring and biometric security. This work presents an energy-efficient photoplethysmography (PPG) processor designed for reliable heart rate estimation and secure biometric authentication. The system integrates advanced sensor interfacing, low-power analog-to-digital conversion, and optimized digital signal processing algorithms to achieve high precision and robustness under diverse operating conditions. Experimental results show that the heart rate estimation algorithm achieves an average error of 1 bpm, corresponding to an accuracy exceeding 98% across varying ambient light and motion artifact scenarios. Concurrently, biometric authentication performance registers accuracies between 96% and 99%, with false acceptance rates below 1.5% and false rejection rates around 2-4%. These results underscore the processor's capability to deliver continuous monitoring and rapid user verification while operating within strict power constraints. Key hardware features such as clock gating and dynamic voltage scaling contribute to extended battery life, supporting prolonged active monitoring and idle operation without compromising performance. The integration of high-fidelity sensors and adaptive filtering techniques further enhances the clarity of the PPG signals, ensuring that critical physiological markers are reliably captured. Overall, the proposed solution meets the demands of modern wearable health monitoring devices by providing real-time performance, high accuracy, and robust security, setting a new benchmark for future developments in low-power biomedical signal processing