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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
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?
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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.
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Example: Lifestyle management
PAL System
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Example: Lifestyle management
5
Some of the Challenges
Emergency ScenarioProduced by CTVC Inc.
6
What Information to Consider?
And how to visualize it?
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Complex user context
Mental context
(interest, focus, etc.)
Availabilitycontext
(people or resource)
Physical context (position, direction,
distance, speed, proximity)
Temporal context
(absolute, relative,
duration)
Activity context
Emotional context
Social context(communication,
identity)
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Visualizations in self-monitoring systems
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Daily story
Visualizations for information collected and derived stored in the personal database
Information collected on demand from remote servers
Calendar-based interface
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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
MindCare20112:30pm. 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
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Overview of Requirements
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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!
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Our Architecture Vision: Information (From) Everywhere
Application
Middleware
Communication
Infrastructure
Components
Netw
ork Aw
areness
Ser
vice
Aw
aren
ess
Information
PolicyFramework
Governance17
Translated into An Architecture
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Visualizations/Interactions
Applications/Services
Middleware
Communication Layer
Policy Engine
DBResourceDiscovery
Component
I/O Component
I/O Component
I/O Component
I/O Component
Data gathering &
transformation
DB
Information modelling and
correlation (Information Agent)
Reasoning Engine
Interaction Manager Visualization Manager
Rendezvous Point
Topology Manager
Policy Agent
PUBPUBPublisher SubscriberSubscriber
Pub/sub Set_
polic
y
Pub/
sub
Set_policyPURSUIT Pub/submap
Map/unmap/divert
Pub/subPub/sub
Pub/sub
Pub/subI/O
Component
Our Approach at Communication Level
ITFITFTopology
RPRP
Rendezvous
RendezvousNetwork
Net
wor
k A
rchi
tect
ure
Service ModelHelper
Error Ctrl
…
Fragmentation
Caching
TMTM
TM TM
Forwarding
ForwardingNetwork Forwarding
Network
ForwardingNetwork
ForwardingNetwork
FN
pubpub
pubsubApps
Nod
e A
rchi
tect
ure
RP : Rendezvous pointITF : Inter-domain topology formationTM : Topology managementFN : Forwarding node
Explorative ApproachEvolutionary Approach
Pub/sub abstraction
TCP
IP
All-Ethernet
wired & wireless
API
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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!
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Gathering Data
Applications
BT
Middleware
IP
Application Server
IP
Android OS
AIRS
BT, BT LEE, RFID,Zigbee
IP
Mobile Device
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”)
Stationary multisensor module A
Embedded Sensors
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Do Users Really Want This?
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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?
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Online survey (preliminary)
• 30 people• Questions focus on:
– Self-reflective behaviours– Building user-friendly interfaces for such systems
• Customizing interfaces• Sharing• Interactions
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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)
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Means for self-reflection
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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)
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System Demo
AIRS & Diary
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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!
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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
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