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Sensor Networks for Medical Care Authors: Victor Shnayder, Borrong Chen, Konrad Lorincz, Thaddeus R. F. Fulford Jones, Matt Welsh Presenter: Velin Dimitrov.

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Presentation on theme: "Sensor Networks for Medical Care Authors: Victor Shnayder, Borrong Chen, Konrad Lorincz, Thaddeus R. F. Fulford Jones, Matt Welsh Presenter: Velin Dimitrov."— Presentation transcript:

1 Sensor Networks for Medical Care Authors: Victor Shnayder, Borrong Chen, Konrad Lorincz, Thaddeus R. F. Fulford Jones, Matt Welsh Presenter: Velin Dimitrov

2 Introduction

3 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 Motivation

4 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 Medical Applications

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

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

7 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 CodeBlue Goals

8 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 CodeBlue – Hardware

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

10 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 Requirements

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

12 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 HIPAA

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

14 Wireless Medical Sensors

15 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 Pulse Oximeter

16 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 EKG

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

18 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 Motion Capture Systems

19 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 Mercury Motion Analysis Board

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

21 CodeBlue Software Architecture

22 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 Publish/Subscribe Routing Layer

23 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_t sendDone(TOS_MsgPtr msg, result_t success); event TOS_MsgPtr receive(TOS_MsgPtr m, uint16_t channel, uint16_t srcAddr); } ADMR

24 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 Multi-Hop/Multicasting

25 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 Calculating Path Cost

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

27 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 Query Interface

28 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 Inefficiencies

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

30 RF Based Location Tracking

31 MoteTrack, Konrad Lorincz, 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 Sharing bandwidth across sensors  Data priority Security  Private Key encryption  Public Key protocol Integration outside of a hospital setting Future Work

42 Progress

43 From 2009 the_wireless_future_of_medicine.html the_wireless_future_of_medicine.html 2:45 minutes

44 Questions/Comments/Discussion

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

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