Sensors implanted inside a body compose so-called intra-body networks (IBNs), which promise high degree of mobility, remote diagnostic accuracy, and the potential of directly activating the action of drug delivery actuators. To enable communication among these implanted sensors, we use the concept of galvanic coupling, in which extremely low energy electrical signals are coupled into the human body tissues by leveraging the conductive prop erties of the tissues. Several challenges emerge in this new communication paradigm, such as how to appropriately mo del the signal propagation through various tissue paths such as from muscle to skin

across different tissue b oundaries and quantify the achievable data rates. The main contributions in this pap er are: (i) we build a 2-p ort tissue equivalent circuit mo del to characterize the b o dy channel and to identify the range of suitable operating frequencies and (ii) we theoretically estimate the channel capacity for various sensor lo cations that incorp orates factors like the tissue propagation path, operating frequency and noise level.

Swaminathan_BodyNets_2014.pdf