Published Paper Details:

This study describes the creation of a real-time signal processing method intended for biomedical wearable devices. The method addresses the essential need for precise, energy-efficient, and effective physiological signal processing in wearable health monitoring devices, including heart rate, oxygen saturation, and electrocardiograms (ECGs). It employs optimal filtering techniques and integrated control mechanisms to provide uninterrupted, real-time monitoring without depleting the device's battery life. In a resource-constrained context, the methodology enhances signal precision and minimizes noise by integrating sensor fusion with advanced signal processing methods. The technology is readily deployable in compact wearable devices due to its optimization for ARM Cortex-M microcontrollers. The research also addresses the algorithm's performance regarding power consumption, computing efficiency, and its capacity to improve patient outcomes in practical applications.