Galvanic coupled CP-BN

January 5, 2018 | Author: Anonymous | Category: Engineering & Technology, Computer Science, Computer Networks
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Intra-body Communication Using Galvanic Coupling Meenupriya Swaminathan, Ferran Cabrera*, Gunar Schirner & Kaushik R. Chowdhury {meenu, schirner, krc}, [email protected] Abstract

Extra-body Network

Proactive Remote care & Lower diagnosis & increased health care care longevity cost

GC Link Sensor


Data Retrieval

Couple r Groun d

Couple r Groun d

Topology Node B Couple r Groun d

Implanted node On Surface node Relay Controller Relay to Controller GC Link Node to Relay GC Link RF Link

Components and Network Architecture for Galvanic Coupled Body Network

Galvanic Coupling - Background

Signal Propagation Through Tissue – Modeling Method

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

Guiding signal through body

Establishing path from node to controller

Physical Protocol Link Quality Analysis


& suffer losses 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].

Self Adaptation


Protocol Design at Network Layer

The 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

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

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

Optimizing Node Placement

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

Why Galvanic Coupling

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 Galvanic Coupling RF

 Studying the impact of realistic noise figures on capacity

Node C Rate Adaptation, Scaling


Storage & Fault Detection Queuing

Data Aggregation

RF Link

Intra-body Network

Memory Signal Processi ng


Signal Processi ng



Couple r Groun d

Human Body GC Link

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

Node A


Data Aggregation

Channel Capacity



Signal Processi ng

RF Link

Data Transfer

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

Couple r Groun d

Signal Processi ng

Data Transfer

 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

RF Transceive r Memory Signal Processi ng

Access Point

Data Retrieval

Implementation of Physical Layer

Skin Fat Muscle

Multiplexing, Synchronization Channel Access & Topology control

Objective – Networking Body Sensors

Traffic to/from node A Traffic to/from node B Traffic to/from node C

Access Point

Channel Model GC Link, Topology, Modulation

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.

Future Research Challenges

 Obtained an estimate for observed noise and achievable data rates.

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

 Identified optimal transmission frequency and electrode placements under varying tissue dimensions [2]

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

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

References [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). Channel gain for on skin links

[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. *Universitat Polit`ecnica de Catalunya, Barcelona, Spain

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