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Wireless Technology and System Integration inBody Area Networks for m-Health Application
Emil JovanovElectrical and Computer Engineering Dept.
University of Alabama in Huntsvillehttp://www.ece.uah.edu/~jovanov
email: [email protected]
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Introduction
mHealth– special issue of IEEE Transactions on Information
Technology in Biomedicine, Dec. 2004, M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity
– Mobile computing– Sensor technology– Communication technologies
WBAN – emerging integration technology– Promising technology for unsupervised, continuous,
ambulatory health monitoring – Challenge: design WBAN for extended real-time
monitoring of physiological data and events.
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WBAN: MotivationGoal: ubiquitous and affordable healthcareConditions: demographic and technology trends– Informal caregivers (1/3 in the U.S.)
Solution: 3-tier ubiquitous monitoring system– Tier 1: Wireless Body Area Network (WBAN)– Tier 2: Personal Server– Tier 3: Healthcare Provider Servers/Medical Servers
Opportunities: – Ambulatory health monitoring– Computer-assisted rehabilitation– Augmented reality systems
Long-term benefits:– Promote healthy lifestyle– Seamless integration of data into personal medical
records and research databases – Knowledge discovery through data mining
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WBAN – design goals
minimization of weight and size of sensors,user’s acceptance,portability,unobtrusiveness,ubiquitous connectivity,reliability, and seamless system integration.
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Wireless technologies
WLAN and WPAN technologiesBluetooth– Widespread, cell phones/PDAs– 720 kbps– Relatively high power consumption, protocol stack
complexity ZigBee– Emerging standard– Very low power– 250 kbps
UWB– High bandwidth
Alternative solutions– MEMS resonators (100 µW)
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Ubiquitous Health Monitoring
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InternetInternet
S S S S
MS
HS
PS
Sn
NCWBAN
WLAN
S S S SSn
WBAN
InternetInternet
MS
HSNC
Sn
InternetInternet
S S S S
MS
PS
WBAN
WAN
NC
WBAN Configurations
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3-tier Hierarchical Organization
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Hierarchical organization
Internet connectivity
WAN communication
Peripherals, timers, etc.
Other
~ 100 W~ 100 mW1-10mW proc.~50mW comm.
Power consumption
~ TB~ 1 GB10-100 KB,1 MB (flash)
Secondarymemory
~ GB~ 50 MB1-10 KBRAM
~ GIPS~ 100 MIPS1-10 MIPSProcessingPower
3. Medical server
2. Personal server
1. SensorTier
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Wireless Body Area Networks at UAH
2000: Wireless Intelligent Sensors (WISE)
2002: Distributed Wireless System for Stress Monitoring
2004: ActiS – Activity Sensor– Standard sensor platforms and
communication protocols“A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation,” Journal of NeuroEngineering and Rehabilitation, http://www.jneuroengrehab.com/content/2/1/6
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ActiS: Activity Sensor
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ActiS: Activity Sensor
ADXL202Accelerometer
ADXL202Accelerometer
ECG SignalConditioning
TI MSP430F1232
CC2420(ZigBee)
Flash
USB Interface
TI MSP430F149
TelosISPM
ECG electrodes
ActiS asMotion Sensor
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Telos Wireless Platform
8MHz Texas Instruments 16-bit MSP430F1611 microcontroller – 10KB RAM, 48KB Flash
Chipcon 2420, IEEE 802.15.4 compliant wireless transceiver – Hardware link layer encryption and
authentication– 250kbps, 2.4GHz– programmable output power
Onboard antenna– Range: 50 m / 125 m
Integrated – humidity, temperature, and light sensors– ADC, DAC, DMA,Supply Voltage Supervisor
TinyOS support
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Intelligent Signal Processing Module ISPM
4MHz Texas Instruments 16-bit MSP430F1232 microcontroller (256B RAM, 8KB ROM)Multiple Dual Axis Analog Devices ADXL202 AccelerometersOn-board bioamplifier (ECG, EMG) Texas Instruments INA321 Instrumentation Amp. Force resistor signal conditioning circuit– Foot switch
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ZigBee network controller
Wireless gatewayARM7 processor~60MIPS proc. power64KB RAMCompact Flash interfaceZigBee wireless interface
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ActiS: Signal Processing
46 46.5 47 47.5 48 48.5 49 49.5 50 50.5 51
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
Accelerometer based step recognition
Time[s]
Vy[m/s]Alpha[rad]accY[g]StepFoot switch
Step detected
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Actis System Performance
1 mW
256B
1 MIPS
1. Signal Processing Module
~ 300 mW60 mW3mW Power consumption
~ 64MB64 KB10 KBRAM
~ 100 MIPS60 MIPS1 MIPSProcessingPower
4. Personal Server
3. Wireless Gateway
2. SensorPlatform
Tier
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System Design IssuesExtremely low-power, low-weight, and small sizeNon-invasive and unobtrusive operationReliable transmission using retransmissionsTime-stamping for collective processing and out of order message processingInteroperability requires standardization– Seamless connectivity– Application specific standards for wireless
communications, messaging, and system supportSeamless customization, configuration, and integrationSensor placement and mounting– Sensor commodization
Security and Privacy – Communication and data storage
Effective user interfaces
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Time Synchronization
Necessary for collective processing, data logging, power-efficient operation, etc.Problem:– High precision synchronization with low
frequency clocks • 32 KHz on Telos
FTSP FloodingTime synchronization protocols– Telos specific implementation at UAH– Implemented precision ~2 µS with 32KHz
crystal!
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Mechanism for Time Synchronization
Propagation
MAC Protocol DataLengthSFDPreamble TimestampData received
over RF
SFD Capture Timer
Synchronize local time(TinyOS)
NetworkCoordinator
Data transmitted over RF
MAC Protocol DataLengthSFDPreamble
SFD Capture Timer
Timestamp
Process Send
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Power Consumption
User’s convenience– Battery life– Size and weight of
batteriesBattery Life– Battery Capacity [mAh] – BL = BC / Iave– For simple time keeping
and minimal processing average power is ~2.1µA, standard 750 mAh batteries will allow battery life:
– BL = 750 mAh / 2.1 µA ≈ 44 years !!!
Introducing:Apple Computers
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Power efficient communication
Wireless communication requires ~ 10 times more power than processing– Turn-off radio whenever you can
Time slots– Time slot scheduling– Allow time slots for new sensors to join the
clubDesign issues:– Battery life– Latency– Number of sensors
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Power efficient wireless communication - implementation
Super cycle time in this example is 1 sec. Sensors listens at the beginning of each cycle for 50ms, and transmits its own messages (2 in this example) in predefined time slot.
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50
5
10
15
20
25
Time [sec]
I [m
A]
0.65 0.7 0.75 0.8 0.85 0.90
5
10
15
20
Time [sec]
I [m
A]
Listen Transmit
Idle
Power supply current on sensor
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Personal Server program
Implemented on PC/PDAControls the network of wireless sensorsCollects data from sensors Communicates with servers on higher levels of hierarchy whenever the connection is availableProvides feedback and alerts to the userStores user’s inputs
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ActiS Monitor – User’s Info
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ActiS Monitor – Network health and Statistics
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ActiS Monitor – Network Control
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ActiS Monitor – Symptoms
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ActiS Monitor – Alerts
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Actis Demo
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ActiS Monitor – Signals and Graphs
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Software Organization
ISPM Software– Physiological sensor interface– Preprocessing of signal data– Resource constrained, no operating system
Telos Software– Developed in component framework of TinyOS– Significant signal processing – Defines Sampling Frequency– Server WBAN Communication
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Wireless Integration
Raw data
Events
MS
Internet Gateway
PS
Sn
NC
WBAN
WLAN/WAN
S S S
InternetInternet
Records
Record collections
Database
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101001…..
Raw Data
Data is written to
permanent storage
File
1Fi
le 2
File
3…
Update Queue
Destination
Connection Made
Record Update Mechanism
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EMR
…Update
Session 1Update
Session 2
Contiguous Data Blocks
System organization - Sessions
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Privacy and Security
Hardware encryption of wireless communicationsStandard security mechanisms from the personal server to the upper levels of hierarchyEMBC05 paper: “Interoperability and Security in Wireless Body Area Network (WBAN) Infrastructures”
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ConclusionsPromising technology for – Ambulatory monitoring– Early detection of abnormal conditions– Supervised rehabilitation
Advantages– Increased confidence and better quality of life– Promotes healthy lifestyle / health awareness– Data mining of huge research databases
• Effects of drug therapies and rehabilitation procedures
Need for standards for wireless communications, messaging, and system support
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Acknowledgments
Aleksandar Milenkovic, Chris Otto, Corey Sanders, John Gober, Reggie McMurtrey, University of Alabama in HuntsvillePiet de Groen, Bruce Johnson, Mayo ClinicSteve Warren, Kansas State University