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Design and Implementation of an Ultra Low Power Health Monitoring Node for Wireless Body Sensor Network

Digital Manufacturing and Automation(2013)

Cited 8|Views12
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Abstract
The human body consists of many complicated physiological signals such as blood pressure, electrocardiograph (ECG), respiratory rate, electroencephalograph (EEG), arterial oxygen saturation (SpO2), body temperature and so on, which, to some extent, reflects the health conditions of the people. Long term and continuous monitoring of these signals are of much importance for the detection and treatment of many diseases such as heart failure, hypertension, diabetes mellitus, etc. Wireless body sensor network is developed in this context and soon become very popular for its convenience and inexpensiveness. In this paper, we introduced the basic knowledge and techniques for low-power health monitoring nodes design, and then we described the design and implementation of an ultra low power ECG (LPECG) monitoring node for wireless body sensor network. We mainly discussed the hardware and software design of the low-power ECG monitoring node, and then we test the power consumption of the node when it working at different modes and the monitoring function of the node is tested and the results are presented, at last, we get the conclusion and pointed out the future development of the node.
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Key words
electrocardiography,respiratory rate,biomedical telemetry,medical signal detection,blood pressure,spo2,people health conditions,ultralow-power health monitoring node design,arterial oxygen saturation,patient monitoring,disease treatment,ecg monitoring,node power consumption,hypertension,node monitoring function,body sensor networks,hardware,electroencephalograph,diabetes mellitus,ultra low power,hardware-software codesign,software,long-term monitoring,hardware-software design,ultralow-power ecg monitoring node,disease detection,wireless body sensor network,eeg,physiological signals,low-power ecg monitoring node,continuous monitoring,heart failure,electrocardiograph,body temperature,automation,manufacturing
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