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Open AccessArticle

Ultra Low Power Signal Oriented Approach for Wireless Health Monitoring

Department of Electrical and Electronic Engineering, University College Cork, Cork 11111, Ireland
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Sensors 2012, 12(6), 7917-7937; https://doi.org/10.3390/s120607917
Received: 27 March 2012 / Revised: 29 May 2012 / Accepted: 29 May 2012 / Published: 8 June 2012
(This article belongs to the Special Issue Body Sensor Networks for Healthcare and Pervasive Applications)
In recent years there is growing pressure on the medical sector to reduce costs while maintaining or even improving the quality of care. A potential solution to this problem is real time and/or remote patient monitoring by using mobile devices. To achieve this, medical sensors with wireless communication, computational and energy harvesting capabilities are networked on, or in, the human body forming what is commonly called a Wireless Body Area Network (WBAN). We present the implementation of a novel Wake Up Receiver (WUR) in the context of standardised wireless protocols, in a signal-oriented WBAN environment and present a novel protocol intended for wireless health monitoring (WhMAC). WhMAC is a TDMA-based protocol with very low power consumption. It utilises WBAN-specific features and a novel ultra low power wake up receiver technology, to achieve flexible and at the same time very low power wireless data transfer of physiological signals. As the main application is in the medical domain, or personal health monitoring, the protocol caters for different types of medical sensors. We define four sensor modes, in which the sensors can transmit data, depending on the sensor type and emergency level. A full power dissipation model is provided for the protocol, with individual hardware and application parameters. Finally, an example application shows the reduction in the power consumption for different data monitoring scenarios. View Full-Text
Keywords: wireless body area network; wake up receiver; mHealth wireless body area network; wake up receiver; mHealth
MDPI and ACS Style

Marinkovic, S.; Popovici, E. Ultra Low Power Signal Oriented Approach for Wireless Health Monitoring. Sensors 2012, 12, 7917-7937.

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