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VLSI based Adaptive Power Management Architecture for ECG Monitoring in WBAN


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Abstract


IoT based standalone ECG systems are emerging as smart health care measures for the detection and prevention of cardiovascular diseases. As most of these systems are batteryoperated, power hungry transmission links reduce the overall lifetime of the entire system considerably. In this paper, a power management strategy and corresponding VLSI architecture is proposed to enhance the lifetime of battery operated IoT based ECG monitoring system. Based on the energy level of the battery, the proposed power management technique automatically adjusts between two transmission modes i.e. high power mode and low power mode. As on-node localized processing is resource-limited, a lightweight algorithm emphasizing slope enhancement with runtime adaptive thresholding is proposed, for real-time detection of QRS complex and evaluation of heart rate, ensuring optimal utilization of power during low battery level. Based on the battery level and heart rate stability, the appropriate transmitting mode is selected which effectively fulfil the goal of Wireless Body Area Network (WBAN) system i.e. collection of enough ECG samples from a single patient as well as improvement of the system lifetime. The sensitivity and predictivity are assessed for the proposed algorithm with MITBIH arrhythmia database and found to be 99.35% and 99.38%, respectively. The architecture has been implemented in Spartan- 6 FPGA with a maximum clock frequency of 269 MHz with a power consumption of 0.7 mW; making it suitable for real-time ECG monitoring systems.

KeyWords
Internet of Things (IoT), Power management, Wireless body area network (WBAN)



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