Development of Real-Time Signal Processing Algorithm for Use in Biomedical Wearable Device

Abstract

This paper presents the development of a real-time signal processing algorithm for use in biomedical wearable devices. The algorithm tackles the vital requirement for accurate, low-power, and effective physiological signal processing in wearable health monitoring systems, including heart rate, oxygen saturation, and electrocardiograms (ECGs). It makes use of optimum filtering methods and embedded control systems to guarantee continuous, real-time monitoring without shortening the battery life of the device. In an environment with limited resources, the algorithm improves signal accuracy and noise reduction by combining sensor fusion with sophisticated signal processing techniques. The implementation can be easily deployed in small wearable devices because it is optimized for ARM Cortex-M microcontrollers. The performance of the algorithm in terms of power consumption, computational efficiency, and its potential to enhance patient outcomes in practical applications are also covered in the study.