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Sensor Networks for Medical Care

Sensor Networks for Medical Care. Authors: Victor Shnayder , Borrong Chen, Konrad Lorincz , Thaddeus R. F. Fulford Jones, Matt Welsh. Presenter: Velin Dimitrov. Introduction. Motivation. Why do we need WSNs in medicine Continuously monitor patients long term

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Sensor Networks for Medical Care

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  1. Sensor Networks for Medical Care Authors: Victor Shnayder, Borrong Chen, KonradLorincz, Thaddeus R. F. Fulford Jones, Matt Welsh Presenter:VelinDimitrov

  2. Introduction

  3. Motivation • Why do we need WSNs in medicine • Continuously monitor patients long term • Emergency/Disaster Scenario • “Active Triage Tag” • Immediate life-critical notifications • Augment/replace existing wired telemetry systems • Improve overall care of patients

  4. Medical Applications • Real time continuous patient monitoring • In-Hospital setting • Home Monitoring – Elderly/Chronic • Continuous data • Long term care/trend analysis • Collection of clinical data Adapted from Matt Welsh’s presentation on CodeBlue at UCSD

  5. Current Implementations • Stationary nodes with low data rates to central station • Improvements • High Data Rates • Reliable communications • Multiple receivers • In-network aggregation cannot be used

  6. Current Implementations • Wireless medical monitors • EKG • Pulse Oximeters • Fetal Heart Rate • Maternal Uterine • “Cut the cord” implementations • Bluetooth, WMTS, Wi-Fi • Systems do not scale well

  7. CodeBlue Goals Develop tiny, wearable, wireless sensors for medical care and disaster response Scalable, robust wireless communication protocols Integrate real-time sensor data into medical care Explore a range of clinical applications Adapted from Matt Welsh’s presentation on CodeBlue at UCSD

  8. CodeBlue – Hardware Sensor modules compatible with Mica2, MicaZ, and Telos mote designs Pulse Oximeter Two lead electrocardiogram (EKG) Motion analysis sensor SFF Telos design for wearable use telosb_datasheet_rev 20111109 (1).pdf

  9. CodeBlue - Software • Device Discovery • Publish/Subscribe multi- • hop routing • Query interface – simplicity • RF-based localization • Low power Bluetooth and 802.15.4 (WPAN)

  10. Requirements • Wearable Sensor Platform • “…large batter packs and protruding antennas are suboptimal for medical use.” • Small, Lightweight, Wearable sensors • Reliable Communications • Data Availability • How much packet loss is acceptable? • Sample rates vary 1Hz to 10’s kHz

  11. Requirements • Multiple Receivers • Multicast capabilities • Device Mobility • Multi-hop routing • Device Discovery • Security • Health Insurance Portability and Accountability Act

  12. HIPAA A review of the implementation of the HIPAA Privacy Rule by the U.S. Government Accountability Office found that health care providers were "uncertain about their legal privacy responsibilities and often responded with an overly guarded approach to disclosing information...than necessary to ensure compliance with the Privacy rule". Wilson J (2006). "Health Insurance Portability and Accountability Act Privacy rule causes ongoing concerns among clinicians and researchers". Ann Intern Med

  13. Related Work • Disaster Response Research • Funded US National Library of Medicine • SMART • AID-N • WiiSARD • Centralized systems • Reliability and Scalability Concerns

  14. Wireless Medical Sensors

  15. Pulse Oximeter • Mature technology (1970s) • Measures heart rate and SpO2 • Catch hypoxemia before visible symptoms • Array of Infrared LEDs • Array of IR detectors • 650nm and 805nm • BCI Medical Micro-Power Pulse Oximeter

  16. EKG • Two different types • Standard EKG • 30 sec of data from 12-15 probes • Diagnose wide range of cardiac arrythmias • Continuous EKG • 2-3 probes • Diagnose intermittent problems

  17. Mote-Based EKG Single pair of electrodes INA321 CMOS instrumentation amplifier 94dB CMRR Gain of 5 TinyOS samples at 120Hz

  18. Motion Capture Systems Parkinson's Disease and Stroke Wired systems with many wires carried in a waist harness Sensors are placed on limbs of interest Accelerometers Gyroscopes EMG

  19. Mercury Motion Analysis Board Wireless 3 Axis Acc – STMicroelectronics 1 Axis Gyro – Analog Devices 1 EMG unit – Motion Lab Systems One mote is placed on each segment of interest

  20. Pluto Mote • Mica2Dot • No 802.15.4 • Pluto • TI MSP430 • ChipCon CC2420 radio • 120 mAh Li-Ion battery • Mini USB

  21. CodeBlue Software Architecture

  22. Publish/Subscribe Routing Layer • Sensors publish data to relevant channel • Requirements • Requested data rates/local filters to limit bandwidth • Multi-hop routing • Mobility of senders/receivers in calculation of routing paths

  23. ADMR • Adaptive Demand-Driven Multicast Routing interface PubSub { command result_t publish(uint16_t chan); command result_t subscribe(uint16_t chan); command result_t leave(uint16_t chan); command result_t send(uint16_t channel, uint8_t length, TOS_Msg* msg); event result_tsendDone(TOS_MsgPtrmsg, result_t success); event TOS_MsgPtr receive(TOS_MsgPtr m, uint16_t channel, uint16_t srcAddr); }

  24. Multi-Hop/Multicasting • Implemented by forwarders • Rebroadcasts messages to a given channel with duplicate suppression • Route discovery • Node table indexed by Publisher ID • Each entry has path cost and previous hop to the publisher • Path costs are updated continuously

  25. Calculating Path Cost PDR – path delivery ratio CC2420 radio provide Link Quality Information (LQI) LQI mapped to Link Delivery Ratio (LDR) Summed for the path making PDR Link Cost is 1-PDR or Path Loss Ratio PDR is held and updated in the header of the ADMR messages

  26. Discovery Protocol • Very simple • Periodically all nodes broadcast metadata • Node ID • Sensor types • Receivers subscribe to the broadcast channel

  27. Query Interface CBQ query are supplied by the GUI Instructs CB to publish data to a specific channel that meets query conditions S – Node IDs Tau – Sensor Type Rho – Sampling Rate Chan – Channel to publish to C – Total Number of Samples

  28. Inefficiencies ADMR and CBQ are separate Simplifies CBQ protocol Inefficiencies arise that ADMR and CBQ both flood the network with broadcast requests CBQ may not be sufficient in all situations but is for most

  29. Sensor Interface Generic interface for sensors getData() dataReady()

  30. RF Based Location Tracking

  31. RF Based Location Tracking MoteTrack, KonradLorincz, Harvard University

  32. User Interface

  33. Evaluation

  34. Scalability - Location

  35. Scalability – 1 Reciever

  36. Scalability – 3 Receivers

  37. Fairness

  38. Packet Jitter

  39. Mobility

  40. Multiple Transmit Packets

  41. Future Work • Sharing bandwidth across sensors • Data priority • Security • Private Key encryption • Public Key protocol • Integration outside of a hospital setting

  42. Progress

  43. From 2009 http://www.ted.com/talks/eric_topol_the_wireless_future_of_medicine.html 2:45 minutes

  44. Questions/Comments/Discussion

  45. Questions What characteristic make this a CPS? What potential challenges exist in the successful real-world implementation of CodeBlue? How does the boom in smartphonesand ubiquitous computing help CodeBlue or does it make it obsolete? Is current encryption technology adequate to secure the system?

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