'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
"(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."Biomedical implantable sensors transmitting a variety
of physiological signals have been proven very useful in the
management of chronic diseases. Currently, the vast majority of
these in-body wireless sensors communicate in frequencies below
1 GHz. Although the radio propagation losses through biological
tissues may be lower in such frequencies, e.g., the medical implant
communication services band of 402 to 405 MHz, the maximal
channel bandwidths allowed therein constrain the implantable
devices to low data rate transmissions. Novel and more sophisticated
wireless in-body sensors and actuators may require higher
data rate communication interfaces. Therefore, the radio spectrum
above 1 GHz for the use of wearable medical sensing applications
should be considered for in-body applications too. Wider channel
bandwidths and smaller antenna sizes may be obtained in frequency
bands above 1 GHz at the expense of larger propagation
losses. Therefore, in this paper, we present a phantom-based radio
propagation study for the frequency bands of 2360 to 2400 MHz,
which has been set aside for wearable body area network nodes,
and the industrial, scientific, medical band of 2400 to 2483.5 MHz.
Three different channel scenarios were considered for the propagation
measurements: in-body to in-body, in-body to on-body, and
in-body to off-body.We provide for the first time path loss formulas
for all these cases.Chavez-Santiago, R.; García Pardo, C.; Fornés Leal, A.; Vallés Lluch, A.; Vermeeren, G.; Joseph, W.; Balasingham, I.... (2015). Experimental Path Loss Models for In-Body Communications Within 2.36-2.5 GHz. IEEE Journal of Biomedical and Health Informatics. 19(3):930-937. doi:10.1109/JBHI.2015.2418757S93093719
