FPGA-Based Smart Health Monitoring Systems for Wearable Devices

Abstract

As wearable technology has expanded at an accelerated rate, FPGA-based solutions have emerged as the preferred approach for constructing cutting-edge health monitoring systems using Xilinx Spartan-7 model FPGA. Their remarkable performance and energy efficiency are the reasons for this. This study investigates the design, implementation, and management of intelligent health monitoring systems for ubiquitous devices that utilize field-programmable gate arrays (FPGAs), with an emphasis on the processing and analysis of real-time data. For real-time data analysis and feature extraction, the proposed system incorporates numerous physiological sensors, including an electrocardiogram (ECG), inertial measurement units (IMUs), and photoplethysmography (PPG), and utilizes an FPGA. An analog front-end for signal conditioning, an FPGA for algorithm execution, and efficient communication interfaces for data transport are all critical elements of the system architecture. Methods for increasing power efficiency, such as clock gating, enable a substantial reduction in CPU throughput while maintaining a high level of power consumption. This provides evidence that the system can perform real-time analyses with minimal latency, enabling continuous and accurate health monitoring. FPGA-based systems outperform conventional microcontroller-based systems about latency, battery consumption, and throughput. The findings of this study establish a foundation for the expanded implementation of field-programmable gate arrays (FPGAs) in ubiquitous health monitoring systems and the possible utilization of this technology for individualized health management.