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Engineering the Cure
Engineers’ attempt to fight diabetes
 An Engineer’s Perspective
 Real-Time
 Real Problems
 A Real Solution
Outline
 Everything can be modeled as a system
 A system has an input
 A transfer function
 And an output
An Engineer’s Perspe...
 Body changes Transfer function changes
 Mapping transfer functions to body changes allows
engineers to estimate differe...
 Machine learning “outsources” the chemistry
 Let the computer make sense of the data
 During a learning stage the mach...
Machine Learning
 Moving from the lab to a product – new challenges
 Real time performance
 Power consumption issues
 Dealing with the ...
Real Problem
Real Problem
 Dozens of millions can not afford glucose testing
 Testing strips can cost up to 100$ a month
Real Solution
 Using Infrared light we construct a transfer function
 No Needles, No Testing Strips
 Machine learning a...
Real Solution
 Glucose monitoring is just one problem
 Intel’s Edison can help solve many more
 Just input the transfer...
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Intel® IoT Webinar - Engineering the cure

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The presentation of the Diabetes Helper, a revolutionary device using the Intel Edison Development platform in the health sector

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Intel® IoT Webinar - Engineering the cure

  1. 1. Engineering the Cure Engineers’ attempt to fight diabetes
  2. 2.  An Engineer’s Perspective  Real-Time  Real Problems  A Real Solution Outline
  3. 3.  Everything can be modeled as a system  A system has an input  A transfer function  And an output An Engineer’s Perspective
  4. 4.  Body changes Transfer function changes  Mapping transfer functions to body changes allows engineers to estimate different parameters:  Oxygen levels  Glucose levels  Diseases? Cancer?  It all depends on the transfer function An Engineer’s Perspective
  5. 5.  Machine learning “outsources” the chemistry  Let the computer make sense of the data  During a learning stage the machine creates a model  Then, new data is classified according to the model Machine Learning
  6. 6. Machine Learning
  7. 7.  Moving from the lab to a product – new challenges  Real time performance  Power consumption issues  Dealing with the statistical outliers Real Time
  8. 8. Real Problem
  9. 9. Real Problem  Dozens of millions can not afford glucose testing  Testing strips can cost up to 100$ a month
  10. 10. Real Solution  Using Infrared light we construct a transfer function  No Needles, No Testing Strips  Machine learning algorithms map data to glucose levels  Users just need to “plug and play”  Solar powered
  11. 11. Real Solution  Glucose monitoring is just one problem  Intel’s Edison can help solve many more  Just input the transfer function and help save lives

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