Power aware ECG processing for WBAN application

Abstract

In the last few decades, advances in wearable technology revolutionized the health newlinecare sector, initiating IoT-based wireless body area networks (WBAN). WBAN newlinebased autonomous healthcare systems have strengthened the traditional health newlinecare framework through real-time and remote monitoring of different biomedical newline signals via wearable sensor nodes. These real-time health monitoring systems with newline battery-operated wearable nodes are expected to operate over a prolonged dura newlinetion, extracting information of vital physiological parameters from ambulatory newline patients. However, these systems need to be effective in terms of power budget newline and hardware resources for assessing critical medical conditions of patients without newline any interruption. A smart power management system in a battery-operated sensor newline node, is a key for developing a power-efficient WBAN framework. This disserta newlinetion concentrates on designing a power-efficient biomedical sensor node system for newline remote ECG signal monitoring. With the technology scaling, constraints of power newline budget and hardware resources in wearable nodes, become prime challenges to newline deal with. In this dissertation, a power-aware ECG monitoring framework with newline on-node feature extraction architecture is discussed. The dissertation also focuses newline on the design and development of a back-end ECG processor with a key element newline of a power management unit i.e., low dropout regulator. Besides, the proposed newline transmission framework is integrated with efficient data compression schemes to newline reduce transmission power consumption. newline Keywords: WBAN, Sensor node, ECG monitoring, Back-end Processing. newline