[1] ICNIRP (International Commission on Non-Ionizing Radiation Protection). 1998. Guidelines for limiting exposure to time-varying electric, magnetic, & electromagnetic fields (up to 300 GHz).

[2] M Swaminathan, F S Cabrera, G Schirner, and K R Chowdhury, Characterization and Signal Propagation Studies for Wireless Galvanic Coupled Body Sensors, IEEE Journal on Selected Areas in Communications, under review.

[1] ICNIRP (International Commission on Non-Ionizing Radiation Protection). 1998. Guidelines for limiting exposure to time-varying electric, magnetic, & electromagnetic fields (up to 300 GHz).

[2] M Swaminathan, F S Cabrera, G Schirner, and K R Chowdhury, Characterization and Signal Propagation Studies for Wireless Galvanic Coupled Body Sensors, IEEE Journal on Selected Areas in Communications, under review.

Channel gain for on skin links

Intra-body Communication Using Galvanic Coupling

Implanted wireless sensors promise the next generation of health-care by in-situ testing of abnormal physiological conditions, personalized medicine and proactive drug delivery to ensure continued well being. However, these sensors must communicate among themselves and with an external control, which raises questions on how to ensure energy efficient data delivery through the body tissues. Traditional forms of high power radio frequency-based communication find limited use in such scenarios owing the limited penetration of electromagnetic waves through human tissue, and the need for frequent battery replacements. Instead, we propose a radically different form of wireless communication that involves galvanic coupling extremely low power electrical signals, resulting in two orders of energy savings. In this scarcely explored paradigm, there are several interesting challenges that must be overcome including (i) modeling the body propagation channel (ii) identifying the best placements of implants and auxiliary data forwarding nodes (iii) devising scientific methods to characterize and improve channel capacity for

information transfer.To model the human tissue propagating characteristics, we developed a theoretical suite using equivalent circuits using MATLAB and validated through extensive simulations using finite element method. Using these models, we estimated the channel gain and obtained an estimate for achievable data rates. We could also identify the optimal transmission frequency and electrode placements for signal propagation. Our results reveal a close agreement with experimental findings. Further development of suitable physical and higher layer networking protocols that are reliable with minimum latency would make galvanic coupling an attractive technology for future intra-body networks.

Objective – Networking Body Sensors Future health-care relies on autonomous sensing of

physiological signals and controlled drug delivery

Need for implanted cyber –physical body sensor network (CP-BN) that can wirelessly communicate with an external control point

Why Galvanic Coupling

Galvanic Coupling RF

10-6 10-5 10-4 10-3 (J)

Existing RF based BNs not suitable for human tissues containing water consume more power does not propagate inside body tissues

Galvanic coupled CP-BN mimics body’s natural signalling (low frequency signals) low interference as energy is confined within body consumes two orders of magnitude less energy

Lower health care cost

Remote diagnosis & care

Proactive care & increased longevity

Components and Network Architecture for Galvanic Coupled Body Network

Galvanic Coupling on Skin (a) Front View (b) Cross Section

Injects low power electrical signal to the tissues Weak secondary currents carry data to receiver Signal propagates radially across multiple tissues & suffer losses

Galvanic Coupling - Background

We constructed a 2-port equivalent circuit model in MATLAB & FEM based ANSYS HFSS simulation suite of human arm using electrical properties of tissues [1].

Obtained an estimate for observed noise and achievable data rates.

Identified optimal transmission frequency and electrode placements

under varying tissue dimensions [2]

Skin to muscle & intra-muscle links showed lower loss than on-skin links

Signal Propagation Through Tissue – Modeling Method

Building transmitter and receiver circuits with suitable modulation schemes that maximizes transfer rate

Studying the impact of realistic noise figures on capacity

Optimizing Node Placement

Outcome:• Fewer Relays• Energy saving• Higher data-rate

Guiding signal

through body

Establishing path from

node to controller

Objective: Establishing reliable & energy efficient CP-BN physical layer

Channel Capacity

Physical Protocol

Topology

Implementation of Physical Layer

Synchronization

Link Quality Analysis

…CP-BN

Self Adaptation

Future Research Challenges

References

Protocol Design at Network LayerThe spatio-temporal distribution should be analyzed and leveraged for

multiple channel access Eg. TDMA

The network should distinguish critical situations from normal deviations based on correlations derived from routine activities.

Eg. Abnormal Heart rate from heavy activity Vs emergency

Support: U.S. National Science Foundation (Grant No. CNS-1136027)

Acknowledgement

Abstract

Meenupriya Swaminathan, Ferran Cabrera*, Gunar Schirner & Kaushik R. Chowdhury{meenu, schirner, krc} @ece.neu.edu, ferran@nomis.es

*Universitat Polit`ecnica de Catalunya, Barcelona, Spain

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