Wireless%20Sensor%20Networks%20for%20Emergency%20Response

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Wireless Sensor Networks for Emergency Response

• Lindsey McGrath and Christine Weiss

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Agenda

• Introduction
• Components of Wireless Sensor Network (WSN)
• Existing Studies/Applications
• Potential Impact
• CodeBlue
• Challenges
• Conclusion

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Introduction

• Sensor networks offer the medical community the
  capability to capture, process and communicate
  critical data through low-power, low-cost
  wireless devices.
• Applicable to various medical areas such as
  patient monitoring, disaster response, and
  rehabilitation monitoring

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Components of WSN

• Data acquisition network and data distribution
  network monitored and controlled by a management
  center
• Motes containing a tiny amount of CPU/memory
• PDAs and PC-class systems

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Existing Studies/Applications

• Studies
• SMART
• AID-IN
• WiiSARD
• Patient Centric Network
• Agent Based Casualty Care
• Applications
• Habitat monitoring Great Duck Island
• WINS - military

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Potential Impact

• Mass Casualty Events (MCE)
• Active Triage Tag
• Bridge the gap between patient load and available
  resources
• Simultaneous physical environment monitoring
• Tracking first-responder and patients location
  and status
• Creation of valuable medical research data

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CodeBlue

• Harvard University in collaboration with various
  medical facilities introduce CodeBlue
• CodeBlue - An ad hoc WSN Infrastructure for
  Emergency Medical Care
• Goal Enhance first-responders ability to
  access patients on scene, ensure seamless
  transfer of data among caregivers, and facilitate
  efficient allocation of hospital resources

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CodeBlue Infrastructure
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CodeBlue VitalDust

• Wearable wireless pulse oximeter and 2-lead
  Electrocardiogram Monitor (EKG)
• Collect heart rate (HR), blood oxygen saturation
  (SpO2), and hearts electrical activity
• Devices can be programmed to alert medical
  personnel when vital signs fall outside normal
  conditions

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CodeBlue VitalDust Implementation

• Pulse Oximeter
• Mote-based oximeter connector betweenMica2/MicaZ
  mote platform and the BCI Medical board
• Measures the amount of light transmitted through
  a noninvasive sensor attached to the patients
  finger
• How is the data used?

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CodeBlue VitalDust Implementation

• EKG
• Mote-based EKG consists of a custom built
  circuit board attached to aMica2/MicaZ/Telos
  mote
• Measures hearts electrical activity through a
  set of leads attached to a patients heart at a
  rate of 120 Hz
• How is it used?

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CodeBlue Pluto

• Wearable tag wristband
• Stores patient information and tracks patient
  location using radio-frequency (RF) signals
• Mote includes an external push button that can be
  used by a patient to transmit a one-way alert to
  medical staff

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CodeBlue Pluto Implementation

• Pluto
• Based on Telos, containsa TI microprocessor,
  ChipCon radio, rechargablebattery and a Mini-B
  USBconnector
• Provides Telos capabilities sacrificing
  expandability and long battery life in favor of
  smaller, light-weight design
• How is it used?

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CodeBlue MoteTrack

• Two-phase process to estimate locations
• Offline collection of RF signal signatures
  followed by online location estimation
• Operates in decentralized, robust fashion
  providing good location accuracy despite minimal
  failures in its infrastructure

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CodeBlue MoteTrack Implementation

• MoteTrack
• Operates using low power, single chip radio
  transceivers located in sensor network nodes
  embedded in a wearable sensor
• Receives messages as signatures from beacon nodes
  populating an area
• How is it used?

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Challenges

• Communication Challenges
• Secure, reliable, ad hoc communication among
  groups of sensors and mobile devices
• Prioritize transmission of data
• Computational Challenges
• Computational power
• Security and encryption techniques
• Programming Challenges
• Level of software services

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Conclusion

• Extremely beneficial in disaster response
  scenarios
• Requires efficiency and accuracy improvement
• A step up in saving lives, creating valuable
  medical research data, and allocation of medical
  resources

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Resources

• Division of Engineering and Applied Sciences,
  Harvard University
• CodeBlue Wireless Sensor Networks for Medical
  Care
• http//www.eecs.harvard.edu/mdw/proj/codeblue/
• Victor Shnayder, Bor-rong Chen, Konrad Lorincz,
  Thaddeus R.F.Fulford-Jones and Matt Welsh. Sensor
  Networks for Medical Care. In the Harvard
  University Technical Report TR-08-05, April 2005
• Konrad Lorincz, David Malan, Thaddeus R. F.
  Fulford-Jones, Alan Nawoj, Antony Clavel, Victor
  Shnayder, Geoff Mainland, Steve Moulton, and Matt
  Welsh. Sensor Networks for Emergency Response
  Challenges and Opportunities. In IEEE Pervasive
  Computing, Special Issue on Pervasive Computing
  for First Response, Oct-Dec 2004.
• Thaddeus R. F. Fulford-Jones, Gu-Yeon Wei, and
  Matt Welsh. A Portable, Low-Power, Wireless
  Two-Lead EKG System. In Proceedings of the 26th
  IEEE EMBS Annual International Conference, San
  Francisco, September 2004.
• David Malan, Thaddeus Fulford-Jones, Matt Welsh,
  and Steve Moulton. CodeBlue An Ad Hoc Sensor
  Network Infrastructure for Emergency Medical
  Care. International Workshop on Wearable and
  Implantable Body Sensor Networks, April 2004.
• Konrad Lorincz and Matt Welsh. A Robust,
  Decentralized Approach to RF-Based Location
  Tracking. Technical Report TR-19-04, Harvard
  University, 2004.