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Outline

Information-centric networking in Healthcare Scenarios Going Beyond Physiological Sensing for Supporting Wellbeing. Work by the PAL project with partners being Cambridge University, Essex University, Thales Research, HW Communications and MAC Ltd

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Outline

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  1. Information-centric networking in Healthcare Scenarios Going Beyond Physiological Sensing for Supporting Wellbeing Work by the PAL project with partners being Cambridge University, Essex University, Thales Research, HW Communications and MAC Ltd User evaluation results by Dana Pavel as presented in MindCare 2011 workshop

  2. Outline • What scenarios do we consider? • What information do we consider? • And how to we visualize the information? • What are the system-level implications & requirements? • Does it really matter? Do users want this?

  3. Example: Lifestyle management Bob is 55 and he has just found out that he has a high blood pressure and he is at risk for developing a serious heart condition in the future unless he makes some adjustments to his lifestyle.

  4. Example: Lifestyle management PAL System

  5. Example: Lifestyle management

  6. Some of the Challenges Emergency Scenario Produced by CTVC Inc.

  7. What Information to Consider? And how to visualize it?

  8. Complex user context Availability context (people or resource) Social context (communication, identity) Mental context (interest, focus, etc.) Emotional context Physical context (position, direction, distance, speed, proximity) Temporal context (absolute, relative, duration) Activity context

  9. Visualizations in self-monitoring systems

  10. Calendar-based interface Daily story Visualizations for information collected and derived stored in the personal database Information collected on demand from remote servers

  11. MindCare2011 10:20am. Location: at home. It’s quiet. Using MS Word, writing in a document called MyPaper_v1.doc. Quite active, it seems, based on how many words per minute you typed. Weather today is cloudy/sunny.

  12. MindCare2011 2:30pm. Location: university. It’s a bit noisy, in a meeting. You are giving a presentation. Getting quite agitated, it seems. Weather now is cloudy/sunny.

  13. System-Level View Requirements, implications, and approach

  14. Overview of Requirements

  15. Key Issues Here • Vast and diverse amount of information • Security and privacy of utmost importance • Policy-driven, even for informal lifestyle management! • Must work anywhere, anytime and on any device • Often said but difficult to achieve! • Creating an understanding at user level is important • Amended by contextual evidence, if necessary!

  16. Service Awareness Network Awareness Policy Framework Application Middleware Communication Infrastructure Information Governance Components Our Architecture Vision: Information (From) Everywhere

  17. Translated into An Architecture Interaction Manager Visualization Manager Visualizations/Interactions Applications/Services Information modelling and correlation (Information Agent) Policy Agent Reasoning Engine Data gathering & transformation DB Set_policy Pub/sub Pub/sub I/O Component I/O Component Pub/sub DB Pub/sub Pub/sub Resource Discovery Component Map/unmap/divert Policy Engine I/O Component I/O Component I/O Component Pub/sub Middleware map Set_policy PURSUIT Pub/sub PUB Topology Manager PUB Subscriber Rendezvous Point Publisher Subscriber Communication Layer

  18. RP : Rendezvous point ITF : Inter-domain topology formation TM : Topology management FN : Forwarding node Pub/sub abstraction Apps pub sub pub Fragmentation pub Node Architecture Topology ITF ITF Service Model Caching API Helper Rendezvous TCP RP … RP Rendezvous Network ErrorCtrl IP Network Architecture All-Ethernet wired & wireless Forwarding TM TM TM TM FN Forwarding Network Forwarding Network Forwarding Network Forwarding Network Explorative Approach Evolutionary Approach Our Approach at Communication Level

  19. Interesting Points in an All Information-centric Approach • Role of middleware • Pub/sub on routing level already • Policies • Integrating information from lower layers • Discrimination of data at network layer • Policy-based routing based on, e.g., importance • Late binding • Enable anywhere in different ways!

  20. BT, BT LEE, RFID,Zigbee IP Gathering Data Motivation • harvest intelligence out there • commoditize acquisition, shift value to intelligence Technical Highlights • Event-based architecture • Transfers only relevant data • Allows for local & remote sensing • Allows for aggregation done in mobile • Utilizes standard Android APIs • Supports more than 50 ‘sensors’, from BT-attached (AliveTech ECG) over system to logical information (such as mood and weather) • Open source • Available on Android Market (search for “airs trossen”) Application Server Applications Mobile Device Middleware AIRS IP Android OS IP Embedded Sensors BT Stationary multisensor module A

  21. Do Users Really Want This?

  22. User-based evaluations • Online survey available at:http://ieg.essex.ac.uk/myror/survey/intro.php • Ongoing user experiments focusing on: 1. What information is perceived as more useful? 2. What correlations are perceived as more useful? 3. How do people want to interact with the system? 4. How do people want to personalize their story? 5. What events are perceived as meaningful by the user?

  23. Online survey (preliminary) • 30 people • Questions focus on: • Self-reflective behaviours • Building user-friendly interfaces for such systems • Customizing interfaces • Sharing • Interactions

  24. Self-reflective behaviours Q1: Do you often think back about what happened during the day? (Often/Not very often/Never) Q2: Do you think about what triggered a certain emotion or behaviour? (Yes/No) Q3: Do you usually propose any change based on self reflection? (Yes/No/Examples)

  25. Means for self-reflection

  26. System-related questions Q6: Would you find useful having a system as presented in the scenario? (Yes/No/Examples of useful information) Q7: If you were to be using such a system would you like to be able to see a story generated based on your activity data? (Yes/No/Explain)

  27. System Demo AIRS & Diary

  28. Conclusions • Lifestyle management is increasingly becoming important • It is an information-driven scenario! • Users not only want this understanding – they want to be in control of it! • Networking-level aspects impact viability of overall scenarios • Late binding and different abstractions important!

  29. Acknowledgements to the Larger Team • Cambridge: Jat Singh, Jean Beacon • Essex: Dana Pavel, Kun Yang, Ken Guild • Thales: Adrian Waller, Glyn Jones, Sarah Pennington • HW: Souroush Honary, Daniel Essafi, Behzad • MAC: Peter Gould, Ying Li • Ericsson: Steve Campbell, Mike Wamsley

  30. Thank you http://www.palproject.org.uk/

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