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Abstract

Remote monitoring of patient vital signs either in hospital or in home provides ease to both patient and hospital staff. It results in less visits of patient to hospital, lesser likelihood of measurements errors, while recording vital sign information. Moreover, due to the rapid ageing in our society, continuous monitoring of the critical patient in home health care is also increasing. Recent progresses in biomaterials, biosensors, wireless communications, and electronic technologies have opened the possibility for designing remote health monitoring devices and technologies. Tracking in real-time the information provided by body surface and internal sensors helps also reduce the invasiveness of a number of medical procedures such as surgeries, internal delivery of drugs, monitoring the status of human organs, etc. The idea of deploying Wireless Body Area Networks (WBANs) which consists of low-powered sensors and actuators deployed around the human body to enable ubiquitous healthcare by measuring continuously all the physiological data of interest and releasing at the right times the necessary drugs into the body, has received considerable attention [1]. However, implementation of the remote healthcare vision comes with many challenges. One of the most important challenges is the characterization and modelling of the in-vivo wireless communication channels, since the health information must be collected from the sensors implanted inside the human body and transmitted wirelessly to the nearby hospital. The characteristics of in-vivo channel are different from wireless free-space communication channel and are due to the fact that the electromagnetic waveforms are propagating through different media that exhibit totally different electrical properties, the wave propagation speed being significantly reduced in organs relative to free space and presenting different time dispersion coefficients for different organs and body tissues. Also, the far field assumption used to develop channel models for classical RF wireless communications systems will have to be removed and the total electromagnetic field effects including the near-field effects will have to be taken into account due to the proximity of body and its organs to antenna near fields. Understanding the characteristics of in vivo communications channels will help in optimizing the physical layer signal processing and communications techniques, and designing efficient networking protocols that ultimately will make possible the deployment of wireless body area networks and remote health monitoring platforms. In this work, modeling of the in vivo communication channel is presented which involves, parametric and non-parametric channel models based on simulation and measurements. The simulations were carried out by placing a patch antenna inside the chest of the human body model and by transmitting a continuous wave signal at industrial scientific and medical (ISM) band. The receiver antenna was placed at 4 cm from the internal antenna and in the same planar height as the transmit antenna as shown in Fig. 1. References: [1] S. J. Devaraj and K. Ezra, "Current trends and future challenges in wireless telemedicine system," in Electronics Computer Technology (ICECT), 2011 3rd International Conference on, 2011, vol. 4, pp. 417-421.

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/content/papers/10.5339/qfarf.2013.BIOP-058
2013-11-20
2019-11-19
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