A wireless body area network of intelligent motion sensors for

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					A wireless body area network of intelligent motion
sensors for computer assisted physical
rehabilitation

Emil Jovanov, Aleksandar Milenkovic, Chris Otto and Piet C de Groen



                      Presenter : Hyotaek Shim
 Telemedicine System

 Wearable health monitoring systems
  integrated into a telemedicine system
    continuous monitoring as a part of a
     diagnostic procedure
    to support early detection of abnormal
     conditions and prevention of its serious
     consequences
    during supervised recovery from an
     acute event or surgical procedure
 Holter monitors

 Traditional personal medical monitoring
  systems
    only to collect data for off-line processing
 Wires may limit the patient’s activity
  and level of comfort
    negatively influence the measured results
 Continuous monitoring

 Important limitation for wider acceptance
  of the existing systems for continuous
  monitoring
    unwieldy wires between sensors and a
     processing unit
    lack of system integration of individual
     sensors
    interference on a wireless communication
     channel shared by multiple devices
    nonexistent support for massive data
     collection and knowledge discovery
 Integrated research databases

 Records from individual monitoring
  sessions are rarely integrated into
  research databases
    support for data mining and knowledge
     discovery
    relevant to specific conditions and patient
     categories
Wireless Body Area Network




     preprocessing & synchronization
Data flow in an WBAN




Sensor level   Personal Server Level   Medical Service Level
 Sensor Level (1/2)

 ECG(electrocardiogram) sensor for
  monitoring heart activity
 EMB(electromyography) sensor for
  monitoring muscle activity
 EEG(electroencephalography) sensor for
  monitoring brain electrical activity
 A blood pressure sensor
 A tilt sensor for monitoring trunk position
 movement sensors used to estimate user’s
  activity
    A “smart sock” sensor or a sensor equipped
     shoe insole
      • to delineate phases of individual steps
 Sensor Level (2/2)

 Minimal weight

 Low-power operation to permit
  prolonged continuous monitoring

 Seamless integration into a WBAN
    standard-based interface protocols

 Patient-specific calibration, tuning and
  customization

 continuously collect and process raw
  information, store them locally, and
  send them to the personal server
 Bluetooth Disadvantages

 transfer raw data from sensors to the
  monitoring station

 limitation for prolonged wearable
  monitoring
    too complex
    power demanding
    prone to interference
 Zigbee wireless protocol

 High level communication protocols using
  small, low-power digital radios based
    IEEE 802.15.4 standard for wireless personal
     area networks (WPANs)
    targeted at RF applications that require
     a low data rate, long battery life,
     and secure networking
 Personal server level

 Initialization, configuration and
  synchronization of WBAN nodes
 Control and monitor operation of WBAN
  nodes
 Collection of sensor readings from
  physiological sensors
 An audio and graphical user-interface
    early warnings or guidance
 Secure communication with remote
  healthcare provider servers
    Internet-enabled PDA
    3G cell phone
    A home personal computer
 Medical Services

 An emergency service
    If the received data are out of range or
     indicate an imminent medical condition
 The exact location of the patient
    If the personal server is equipped with
     GPS sensor
 monitoring the activity of the patient
    By medical professionals
    Issue altered guidance based on the new
     information
           ActiS : Activity Sensor
            ISPM                              Telos

  ADXL202                                               CC2420
Accelerometer                                           (ZigBee)
                       TI
  ADXL202          MSP430F1232       TI                  Flash
Accelerometer                    MSP430F149
 ECG Signal
                                                      USB Interface
 Conditioning



ECG electrodes


 The Telos platform
    8MHz MSP430F1611 microcontroller
    10KB RAM and 48KB Flash Memory
    UART(Universal Asynchronous Receiver
     Transmitter)
 ISPM
    MSP430F1232 microcontroller
    10-bit ADC and UART
 ActiS : Motion Sensor




 ActiS sensor as Motion Sensor
 Vertical Plane Θ =
    to detection of gait phases
ActiS : Signal Processing
 Conclusion

 Continuous monitoring in the ambulatory
  setting
    early detection of abnormal conditions
     • increased level of confidence
     • improve quality of life
   supervised rehabilitation
   potential knowledge discovery
     • through data mining of all gathered information

				
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