Dario - Fighting and winning the war on diabetes with your iPhone and a mobile glucometer

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Dario is a complete mobile glucose management system based on a smartphone (iPhone or Android) and secure cloud services. Dario offers a number of unique and extremely valuable features such as a standardized glucometer device that attaches to the earpiece of the handset and does not require special cabling. Having a standard device also means that for the first time - diabetes patients can share data with their physicians and physicians can be certain that the data was obtained from the same calibrated device no mater who their Dario patient was.

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  • There is good reason for this – the providers invest in transaction systems to improve their operational efficiency, the cost of water or outbreaks of swine flu are beyond their control – or not?
  • In the US 10.5% of population between 20 and 70. In Israel – 6%. That is NIS 12 BN. The entire 2012 budget of the Ministry of Education was 40BN by comparison.
  • Medicine begins to look very different with apps (and devices connected to the smartphone) that don’t just communicate information, but actually do medicine — diagnostics, telemetry and therapy — on the smart phone or tablet.
  • Dario - Fighting and winning the war on diabetes with your iPhone and a mobile glucometer

    1. 1. Fighting (and winning) the battle of diabetes with M2M M2M conference, Herzliya, Israel June 2, 2013 Danny Lieberman dl@software.co.il Software Associates Software security specialists for biomed
    2. 2. Foreword • Work described in this talk was performed under contract to Labstyle Innovations for the Dario project. • My thanks to Dr. Oren Fuerst CEO and Erez Raphael VP R&D.
    3. 3. In the beginning • In the beginning there was connectivity and hierarchy.
    4. 4. Data center Meter #1145671 The network Meter #8716542 Connectivity Dumb Smart
    5. 5. Hierarchy Doctor Parent Nurse Child Dumb Expert
    6. 6. Hierarchy creates a bottleneck
    7. 7. This is a problem • Data flows 1 way to the provider who accrue most of the benefits. – The water company – Your healthcare provider • Consumers who generate the data don’t get cheaper water or better health
    8. 8. The real problem
    9. 9. Technology Mobile • 1.4 BN smart mobile devices Mobile Medical • Large numbers of consumers with mobile medical devices Search • Large numbers of patients asking Dr. Google or friends on FB
    10. 10. Innovation 101: Data accessibility Cloud data analytics services Device #8217662 Device #1198716 Device #7761543 Big data Smart devices Access to data enables the consumer to make better informed decisions - but there are serious problems of data quality.
    11. 11. Innovation 201 – Data to action Accurate data collected with the same test equipment enables a swarm of devices to be proactive.
    12. 12. Dario: Devices to data to action www.mydario.com
    13. 13. Dario: Devices to data to action Actionable Intelligence All-in-1 Glucometer Mobile App Great data Accessibility Machine learning Proactive treatment Strips, lancet Glucometer, iPhone I/F Blood glucose, Food, Medication, Exercise Data access to caregivers, physicians
    14. 14. System architecture iOS Android RIM Win8 Mobile Clients Product WebSite Commercial WebSite (investors Relations) Web Clients Cloud Side Firmware Dario GM Services(Logic,Monitoring,Localization) DataBases(Medical...
    15. 15. All-in-1 Glucometer
    16. 16. Glucometer components • Basic Adaptor - basic adaptor that connects to the audio jack of a Smartphone; transmits test signal from a blood test strip • Lancing Device–Integrated lancing device that can be loaded with disposable lancet • Strips Cartridge–disposable strips cartridge holding and dispensing 25 test strips. • Mobile device application
    17. 17. Demo • Short guided tour with my iPhone
    18. 18. Caregiver/physician module • Enables a caregiver to track patients and identify the level of compliance with the recommended treatment. • Help identify patients that are in risk and that require a higher level of personal attention at a particular point in time.
    19. 19. Machine learning module • Trains on personal data sets of blood glucose, food intake, insulin dosage and physical exercise. • Implements a novel collaborative approach between user and system • Reinforces patient behavior • Provides proactive feedback in the form of rewards that guide the learning algorithm and the user to achieve better diabetes management

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