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SURVEY FOR WIRELESS SENSORS IN HEALTHCARE

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Title: SURVEY FOR WIRELESS SENSORS IN HEALTHCARE


1
SURVEY FOR WIRELESS SENSORS IN HEALTHCARE
  • Presented by
  • Bharat Soundararajan

2
OUTLINE
  • INTRODUCTION
  • PROPOSED PROBLEMS
  • NETWORKS FOR HEALTHCARE
  • MEDIC AND ITS ALGORITHM
  • DIFFERENT TYPES OF TOPOLOGIES
  • FUTURE

3
INTRODUCTION
  • Patients need continuous monitoring of their
    health conditions
  • Various vital and health care
  • data are collected using
  • sensors and sent to the
  • hospital

4
Proposed Needs
  • Low complexity
  • Low cost
  • Data reliability
  • Low power consumption

5
Different networks for healthcare
WLAN (802.11) Bluetooth-based WPAN (802.15.1) ZIGBEE (802.15.4)
Range 100m 10-100m 10m
Cost/complexity gt6 1 0.2
Power consumption Medium Low Ultralow
Size Larger smaller smallest
6
MEDIC
  • Acquire data from patients in real world
  • It sends data to the centralized server and the
    centralized server forwards data to all the nodes
  • It can be configured from the remote server
  • Wearable sensors to patients for comfort ability

7
MEDIC
MEDICAL PERSONAL
INTERNET
ZIGBEE or BLUE TOOTH
8
What is ZigBee??
  • ZigBee technology is a low data rate, low power
    consumption, low cost, wireless networking
    protocol targeted towards health care
  • Zigbee Alliance introduced Zigbee standard
    protocol in 2003
  • ZigBee is a technological standard, based on the
    IEEE 802.15.4 standard, which was created
    specifically for control and sensor networks. 

9
The Zigbee Protocol Stack
10
What is ZigBee??
  • As can be seen in the figure, IEEE 802.15.4
    develops the Medium Access Control (MAC) Layer
    and Physical (PHY) Layer, which address such
    things as the frequency and data rate
    specifications.
  • ZigBee develops the Network Layer and
    Application Layer, which includes the
    Applications Support Sub layer, the ZigBee Device
    Object, and the Security Services.

11
BAYESIAN NETWORK ALGORITHM
  • A set of variables independent of each other
  • The probability of these variables influence the
    output
  • Symptoms are used to determine whether a person
    has a disease
  • This is trained by the previous data used for
    the treatment

12
BAYESIAN NETWORK ALGORITHM
DISEASE
PULSE RATE
OXYGEN LEVEL
BODY TEMPERATURE
BLOOD PRESSURE
13
PROBLEM WITH MULTIHOP
Cluster Tree
PAN coordinator
Full Function Device
Reduced Function Device
14
Timezone CoordinatedSleep Scheduling Algorithm
(TICOSS)
  • coordinated sleeping through the division
  • of the network into time zones
  • The time zones also provides coordinated
    sleeping, through the V-table scheduling
  • The scheduling table allocates timeslots to nodes
    in order to assign periods of node activity and
    inactivity

15
Topology Models
Mesh
Star
PAN coordinator
Full Function Device
Cluster Tree
Reduced Function Device
16
TOPOLOGY MODELS
  • It manages all the sensors inside the network
  • It collects information from all the nodes and
    forwards it to the centralized server

17
TOPOLOGY MODELS
  • Fully functional device
  • Any topology fits for fully functional
    device
  • It can also act as a network coordinator,
    network router
  • Reduced functional device
  • It only fits perfectly for reduced functional
    device
  • It cannot act as a network administrator

18
Future???
  • ZigBee is seen as a key technology for home
    automation and sensor networks, but its
    characteristics can be extremely valuable in some
    healthcare applications as well.
  • On July 24-27, 2006 in the Free scale Technology
    Forum, Orlando, FL, the wireless developer
    Cambridge Consultants demonstrated how ZigBee's
    unique networking attributes can be exploited to
    implement networks for healthcare.

19
References

1. MEDIC Medical embedded device for individual
careAuthors Winston Wu, Alex A.T.bui, Maxim
A.batalin, Lawrence K.Au,Jonathan D.Binney,
William J.kaiserPublished by Elsevier Science
Publishers Ltd, Essex, UK in 20082. Energy
Efficient Multihop medical sensor
networkingAuthors A. G. Ruzzelli,  R. Jurdak,
G. M.P O'Hare, P. Van Der StokPublished by ACM
Newyork Ny, USA in 20073. An integrated
wireless sensing and mobile processing
architecturefor assisted living and healthcare
applicationsAuthors  S.Dagtas, Y.Natchetoi,
H.WuPublished by ACM Newyork Ny, USA in
20074. Wearable FPGA based Wireless Sensor
platformAuthors Tom Ahola, Pekka Korpinen,
Juha Rakkola1, Teemu Ramo, JukkaSalminen and
Jari SavolainenPublished by IEEE EBMS in
20075. Low-cost wireless sensor networks for
remote cardiac patientsmonitoring
applicationsAuthors  Fei Hu, Meng Jiang, Yang
XiaoPublished by Wireless Communications and
Mobile Computing (WileyInterScience Journal),
(to appear), March 2007.
6. Reconfigurable Point-of-Care Systems Designed
with InteroperabilityStandardsAuthors Steve
Warren, Jianchu Yao, Ryan Schmitz, and Jeff
LebakPublished by  IEEE EMBS in 20047.
Patient monitoring using infrastructure-oriented
wireless LANsAuthors Upkar VarshneyPublished
by International Journal of Electronic
Healthcare, 2006 8. Body Area Network and Its
Standardization at IEEE 802.15.MBANAuthors
Huan-Bang Li, Ken-ichi Takizawa, Bin Zhen, Ryuji
KohnoPublished by National Institute of
Information and Communications Technology9.
Vmote-II, A biowearable health monitoring
systemAuthors Masilela, M.   Hughes, E.A.
Boanca, C. Merrell, R.RafiqPublished by
 Information Technology Applications in
Biomedicine, 2007. 10. Wearable Laser Blood
Flow meter for Ubiquitous HealthcareAuthors
Kiyokura,  Tatara N.,   Shimada. J.,  
Haga.T.Published by  NTT Microsyst.
Integration Lab, Kanagawa
20
THANK YOU
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