Low Power FPGA Implementation of ECG monitoring in WBAN

In smart healthcare, independent ECG devices with an Internet of Things foundation are becoming commonplace for identifying and averting cardiovascular disorders. Nevertheless, since these systems frequently run on batteries, transmission connections with high power consumption might drastically shorten their total operating life. This study suggests a power management approach and related VLSI design to improve the longevity of battery-operated Internet of Things ECG monitoring devices in order to solve this problem. Depending on the battery’s energy level, the suggested approach dynamically switches between high-power and low-power transmission modes. For on-node localized processing, a lightweight technique with a runtime adaptive thresholding focus on slope improvement is presented. This algorithm allows for real-time QRS complex recognition and heart rate evaluation while optimizing power consumption in low battery conditions. By effectively gathering enough ECG data from a single patient and prolonging system lifespan, the suggested system satisfies the objective of Wireless Body Area Network (WBAN) systems by intelligently choosing the suitable transmission mode depending on battery level and heart rate stability. Using the MIT-BIH arrhythmia database, the algorithm’s sensitivity and predictivity were evaluated; 99.35% sensitivity and 99.38% predictivity were obtained. With a maximum clock frequency of 269 MHz and a power consumption of only 0.7 mW, the Spartan-6 FPGA was used to build the design, which made it appropriate for real-time ECG monitoring. IoT-based ECG monitoring systems may now operate more efficiently and last longer thanks to the suggested power management approach and VLSI design, which increases their suitability for real-time healthcare applications.