Wireless Sensor Networks in Healthcare

1
Wireless Sensor Networks in Healthcare
2
Potential and Challenges

• integrate available specialized medical tech.
  with wireless networks (ex wearable
  accelerometers with integrated wireless cards for
  patient monitoring)
• Benefits save on medical expenses, time (less
  face-to-face appointments required), allows more
  participants in clinical trials

3
Requirements

• Interoperability between biomedical devices
  required
• Event ordering, timestamps, synchronization,
  quick response in emergencies required
• Reliability and robustness for making accurate
  diagnoses and proper functioning in uncontrolled
  environments
• Integration of many types of sensors demands new
  node architecture

4
Requirements (cont.)

• Operation in buildings results in further
  interference due to walls, etc. decreasing
  reliability
• Multi-modal collaboration and energy conservation
• Multi-tiered data management
• Privacy of records ownership of information not
  always clear
• Priority override must be carefully designed
• Data available during emergencies
• Realtime role-based access control

5
Acceptance of WSNs by patients

• Especially important for elderly patients
• Tendency to reject technology
• Must be intuitive and easy to operate
• A study in which elderly residents of Sydney
  participated in an open-ended discussion found
• Overall positive view of WSNs due to implications
  for independence
• Ashamed of visible sensors (design as unobtrusive
  as possible)
• Adherence issues due to forgetfulness
• Distrust of technology
• Privacy

6
Implementation

• Sensors various types of wearable biomedical
  sensors with integrated radio transceivers (ex
  accelerometer in bracelet to detect hand tremors)
• Ad hoc network using Zigbee protocol?
• Low power consumption of protocol makes it
  desirable for this application
• Radio signal received by cell phone and
  transmitted to server
• Analysis of raw data performed via wavelet
  analysis
• Decision tree or artificial neural network used
  to decide appropriate action (data is within
  normal range, outside normal range and either
  does or does not require emergency action, etc.)
• Data stored in server side database and report is
  generated to send to healthcare professional

7
Monitoring and Data Transmission

• Monitoring and transmission can occur
  continuously, periodically or be alert-driven
  (case-dependent)
• Transmit differential data to decrease energy
  consumption/traffic
• Priority-based transmission path of transmission
  determined by nature of data, with emergency
  signals receiving highest priority
• Sensors (and potentially other wireless devices
  in the area) form an ad hoc network
• If cell phone fails to transmit data, data can be
  transmitted over multiple hops in ad hoc network
  to travel within range

8
Data Transmission (cont.)

• ZigBee could be appropriate specification for
  networking biomedical devices
• Significantly lower wake up time than Bluetooth
  (15 ms or less vs. 3 s) gt low power consumption,
  long battery life
• Inexpensive transceivers
• Capable of establishing self-forming,
  self-healing mesh networks

9
Motion Detection Wavelet Analysis

• Continuous Wavelet Transform (CWT)- similar to
  Fourier Transform, but with a variety of probing
  functions

• b translates function across x(t) and a varies
  time scale
• ?(t), when b0 and a1, represents mother wavelet
  of a family of wavelets
• problem with CWT - overly redundant and
  extremely difficult to recover original signal

10
Discrete Wavelet Transform

• To limit redundancy, DWT restricts variations in
  translation and scale (often to powers of two)
• Recovery tranformation
• Where a2k, b l 2k, and d(k,l) is a sample of
  W(a,b) at discrete points
• Scaling function
• c(n) is a series of scalars defining specific
  function
• Wavelet
• d(n) is a series of scalars related to x(t)

11
Filter Banks

• Most basic filter bank x(n) is divided into two
  - ylp(n) and yhp(n), using a digital lowpass
  filter H0 and highpass filter H1 respectively

12
Filter Banks (cont.)

• Using this method, twice the points of original
  function must be generated
• Compensate by downsampling
• Signal smoothed by series of low pass filters
• Original signal broken down into frequency bands
  gt useful information about signal can be
  determined