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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 Perspective
 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
 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
Machine Learning
 Moving from the lab to a product – new challenges
 Real time performance
 Power consumption issues
 Dealing with the statistical outliers
Real Time
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 algorithms map data to glucose levels
 Users just need to “plug and play”
 Solar powered
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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Intel® IoT Webinar - Engineering the cure

  • 1. Engineering the Cure Engineers’ attempt to fight diabetes
  • 2.  An Engineer’s Perspective  Real-Time  Real Problems  A Real Solution Outline
  • 3.  Everything can be modeled as a system  A system has an input  A transfer function  And an output An Engineer’s Perspective
  • 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.  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
  • 7.  Moving from the lab to a product – new challenges  Real time performance  Power consumption issues  Dealing with the statistical outliers Real Time
  • 9. Real Problem  Dozens of millions can not afford glucose testing  Testing strips can cost up to 100$ a month
  • 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. 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