1. Wireless Sensor Networks for Emergency Response Lindsey McGrath and Christine Weiss

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

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

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

5. Existing Studies/Applications Studies Studies SMART SMART AID-IN AID-IN WiiSARD WiiSARD Patient Centric Network Patient Centric Network Agent Based Casualty Care Agent Based Casualty Care Applications Applications Habitat monitoring – Great Duck Island Habitat monitoring – Great Duck Island WINS - military WINS - military

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

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

8. CodeBlue Infrastructure

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

10. CodeBlue: VitalDust Implementation Pulse Oximeter Pulse Oximeter Mote-based oximeter connector between Mica2/MicaZ mote platform and the BCI Medical board Mote-based oximeter connector between Mica2/MicaZ mote platform and the BCI Medical board Measures the amount of light transmitted through a noninvasive sensor attached to the patient’s finger Measures the amount of light transmitted through a noninvasive sensor attached to the patient’s finger How is the data used? How is the data used?

11. CodeBlue: VitalDust Implementation EKG EKG Mote-based EKG consists of a custom built circuit board attached to a Mica2/MicaZ/Telos mote Mote-based EKG consists of a custom built circuit board attached to a Mica2/MicaZ/Telos mote Measures hearts’ electrical activity through a set of leads attached to a patients heart at a rate of 120 Hz Measures hearts’ electrical activity through a set of leads attached to a patients heart at a rate of 120 Hz How is it used? How is it used?

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

13. CodeBlue: Pluto Implementation Pluto Pluto Based on Telos, contains a TI microprocessor, ChipCon radio, rechargable battery and a Mini-B USB connector Based on Telos, contains a TI microprocessor, ChipCon radio, rechargable battery and a Mini-B USB connector Provides Telos capabilities sacrificing expandability and long battery life in favor of smaller, light-weight design Provides Telos capabilities sacrificing expandability and long battery life in favor of smaller, light-weight design How is it used? How is it used?

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

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

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

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

18. Resources Division of Engineering and Applied Sciences, Harvard University 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 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. 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. 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. 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. Konrad Lorincz and Matt Welsh. A Robust, Decentralized Approach to RF-Based Location Tracking. Technical Report TR-19-04, Harvard University, 2004.