smart products and connected health the personal metrics movement fredric raab sr. systems engineer...
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Smart Products and Connected Health
The Personal Metrics MovementFredric RaabSr. Systems Engineer
UCSD Center for Wireless and Population Health Systems
The Personal Metrics MovementWired July 2009
Know ThyselfThe personalmetrics movementgoes way beyonddiet and exercise.It’s about tracking every facet oflife, from sleep tomood to pain,24/7/365.
Gary Wolfquantifiedself.com
The Personal Metrics MovementWired July 2009
• Track your data
• Analyze your results
• Optimize your life
• Share with others
Applications
Consumer driven
Performance monitoring
Self improvement
Behavioral change
Wellness
Personal reflection
Health provider driven
Clinical monitoring
Disease management
Remote diagnostics
Aging in place
Research
Components
• Smart devices – Collect, store, upload
• Web-based applications– Storage– Analytics– Visualization– Sharing
• Mobile phones– Intervention and behavior change
Types of data
SensorHeart rate
ECG
Respiration
Body temp
Blood pressure
Glucose levels
Movement (activity)
Steps
Location (gps, wifi)
Self ReportFood intake
Mood
Smoking / drinking
Cravings
Medications
Weight
Level of pain
Consumer applicationsNike+ & Garmin Forerunner
Omron pedometer
GoWear activity monitor
Zeo sleep monitoring
Research toolsHeart rate and activity monitoring
ECG, heart rate, activity, posturerespiration, skin temperature
Clinical real-time monitoring
Clinical real-time monitoring
Chronic disease management
Medication complianceGlowCap
Medication complianceProteus Biomedical
Medication complianceDrug delivery patch
“Band-aid” sensorsCorventis
Implantable sensorsCardiomems
Business challenges
Medical device approval Insurance reimbursement classification code
Technical challenges
• Power efficient radios– Proprietary protocols– Multiple intermediary devices
• Battery life
• Size
• Wearability and compliance
• Connectivity
• Bandwidth
The future
• More devices directly connected
• Smart fabrics– Sensors and power built into clothing
• Pattern recognition and machine learning applied to server-side analytics
• Personalized health intervention systems– Reminders, prompts, suggestions, feedback
