1. Open mHealth and the Center of
Excellence for Mobile Sensor
Data-to-Knowledge (MD2K)
Ida Sim, UCSF + Open mHealth
David Haddad, Open mHealth
Advancing biomedical discovery and improving health through mobile sensor big data
Cornell Tech ♦ Georgia Tech ♦ U. Memphis ♦ Northwestern ♦ Ohio State ♦ Open mHealth
Rice ♦ UCLA ♦ UC San Diego ♦ UC San Francisco ♦ UMass Amherst ♦ U. Michigan

2. Problem 1: more and more digital health tools are coming
to market but their data is trapped in silos.

3. Problem 2: your clinical visit is only a tiny slice of your
health pie. we know that it’s only through the combination
of multiple data streams that we can tell a person’s health
story.

4. Solution: Open mHealth solves these problems by offering
developers and health systems a free and open API to
access digital health data with the right clinical context.
We’re working with a community of developers and clinical
experts to build an infrastructure for digital health.

5. Mission: Unlock the potential of digital health data so it can
be meaningful in the clinical environment.

6. 1.
Translate needs
toolmakers &
clinicians
2.
Open, free
API platform
3.
Build patient-
centered products
what we do

7. Clinical
experts
Tool-
makers
Deploy-
ments
Hypertension
Mental Health
Diabetes
Pain
Symptom
Nutrition
Activity:
● Penn Med
● Stanford
Medication adherence:
● Columbia
Mental health:
● VA
● Intel
● Vermont
Symptom / pain management:
● UC Davis
● UoW
Genetics:
● Global Alliance for
Genomes and Health
(Just a few examples!)
Connections to:
● Fitbit, Jawbone,
Runkeeper, Moves,
Withings, iHealth,
FatSecret, PAM,
Mobility
Building connections to:
● Google Fit
● HealthKit
● MapMyFitness,
● Entra, Agamatrix
● Ginger.io
● etc.
Clinically focused devices:
● nVolve
● Cortrium
● Nutrify, FoodCare
Linq:
● Stanford
● Mass Gen
● Columbia
● NY City
● OSU
MD2K
● 12 top clinical and
CS research
institutions
Trialist:
● UC Davis
● Brown
● UCSF - Health
eHeart

8. Linq is a way for people to collaborate with their doctor around
health tracking using the apps and devices they love

9. Linq features a clinician-facing
dashboard

10. And a patient-
facing mobile
app

11. Brief demo

14. MD2K Mobile Data Science
Goals
• Generate software, tools, data, and science
• To enhance the ability to gather, analyze, and
interpret health-related mobile sensor data,
• Which facilitates the development of innovative
methods for early detection & prevention of complex
chronic diseases
• Share data and tools via Open mHealth
• Establish an mHealth web portal and conduct
annual mHealth Training Institutes

15. Detect Predict Intervene
Driving Clinical Problems: Prevent
Smoking Lapse & Reduce CHF Re-
admission

16. Smoking Cessation Project
• Background: each year, 40% of smokers attempt to quit.
Only 5% succeed. A lapse predicts relapse.

17. CHF Project
• Background: CHF patients have ~30% chance of being readmitted to
hospital within 30 days of CHF discharge.

18. Mobility-related Sensors
• Sensors used in MD2K
– 9-axis wrist sensors: in-house, and Microsoft Band?
– accelerometer on smartphones
• GPS/GIS algorithms from PALMS project
• Would like to be able to use commercial sensors
to increase generalizability

19. Mobility-related Features of Interest
• Sedentary minutes
• Minutes of any non-sedentary activity
• Minutes of moderate activity (3 - 6 METS )
• Minutes of vigorous activity (> 6 METS)
• 6 Minute Walk Test equivalent
• Flights of stairs climbed
• NYHA CHF class (i.e., dypsnea with exertion)

21. MD2K-Mobilize Data/Tool
Sharing
• Open mHealth APIs to commercial devices
– what granularity of data?
– build jointly?
– feedback to companies on what to expose?
• Share algorithms as Open mHealth DPUs
– expose Mobilize algorithms as DPUs?
• Expose computed measures to BD2K and wider
community via Open mHealth schemas

22. Discussion