Transcript Galvanic coupled CP-BN

Intra-body Communication Using Galvanic Coupling
Meenupriya Swaminathan, Ferran Cabrera*, Gunar Schirner & Kaushik R. Chowdhury
{meenu, schirner, krc} @ece.neu.edu, [email protected]
Abstract
Extra-body
Network
Proactive
Remote
care &
Lower
diagnosis & increased
health care care
longevity
cost
GC Link
Sensor
Sensor/Actuator
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
…
CP-BN
& 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
Synchronization
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
CSMA
& BES
Storage & Fault
Detection
Queuing
Data Aggregation
RF Link
Intra-body Network
Memory
Signal
Processi
ng
Relays
Signal
Processi
ng
Relay
Implant
Couple
r
Groun
d
Human Body
GC Link
 Building transmitter and
receiver circuits with suitable
modulation schemes that
maximizes transfer rate
Node A
Controller
Data Aggregation
Channel Capacity
Implant
Controller
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