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Experiences from Assessing Daily
   Activities to Increase Safety and
Comfort of Older Persons Living Alone
     Paul Panek, Peter Mayer, Özge Subasi
            and Wolfgang L. Zagler

 Institute for Design and Assessment of Technology
            Vienna University of Technology
              IFA 11th Global Conference on Ageing
          28 May – 1 June 2012, Prague, Czech Republic
Content


 Introduction and Aim
 Approach
 Results from Fieldtrials
 Conclusion
Introduction & Aim


 Many research papers available about AAL
  systems and activity monitoring
  – But unclear, to what extent such systems can be
    applied in real life
 Therefore - Aim of eHome project:
  – Demonstration of practical usefulness
  – In daily use
  – Basic system with ZigBee based sensors was
    developed
Approach


 Daily life follows certain schedules
   – Given by routine
   – Following social and biological rhythms
 eHome monitors continuously
   – Assessing activities in fixed time slices (e.g. 1 hour)
   – Triggering supportive or emergency actions if
     significant deviations
   – Keeps private data protected inside the user’s home
 Objective of eHome: Improving safety and
  comfort of older persons living alone at home
Approach


 eHome system uses
  – Sensors connected via ZigBee
  – Storing data in a database
  – Data being processed in a small central
    unit
  – Situated at user’s home ( privacy of
    data)
  – Connected to the Internet.
Approach


 Event triggered expert system can raise
 alerts based on:
  – Time of activities
    (e.g. rising from bed compared to daily history)
  – Duration of selected activities
    (e.g. nightly leaving of bed)
  – Frequency of activities
    (e.g. reduction in cooking, hygiene)
Approach


 Assumption of eHome is:
  – Even by applying a rather coarse monitoring by
    a small set of sensors a sufficient insight into the
    user’s activity can be reached
  – Even if “better” and “more” sensors would be
    possible this was avoided in order to
      Increase perspective for economic exploitation
      Improve the to-be-expected user acceptance
Field Trials


 Extensive evaluation with
  – 5 research prototype systems
  – installed in 11 homes of older persons
  – over a total time of 18 months
Field Trials


 ZigBee Sensors for
  – Door / window
  – Acceleration & floor
    vibration
    (e.g. for fall detection)
  – Temperature
  – Cooking plate temp.
    (infrared)
  – Movement (passive
    infrared)
  – Light
Impressions from Field Trials


 Local User Interface
   – Touch-Screen Terminal
     without typical PC look
   – Fits to furniture
   – Easy to use
   – Video telephone
   – Smart-Home Controls
   – Emergency Call
   – Internet Browser
e-HOME – reminders & call for help
e-HOME – easy to use (video) phone
Field Trials
Results


 System was able to classify “usual
 behaviour” over time. This can be used in
 different ways:
  – Unusual sudden changes (e.g. not leaving bed in
    the morning)  triggering alarm
  – mid-term and long-term trends  present
    changes to care persons to let them judge about
    the meaning and severity of recognised
    changes.
Presence in living room 9 July
Results


 The system is able to learn / adapt over time its
  threshold parameters
 Remark: Even right from the beginning the system
  is able to work with initial values  important for
  practical use!
 By adapting over time it will improve performance
Conclusion


 Despite needs for improvement there is evidence
  that the system actually is considered by users and
  experts to have the potential to bring significant
  benefits in supporting older persons and carers.
 eHome prototype currently is used in LLM (CIP)
  and KSERA (FP7) project
 Costs for low quantities of basic eHome system
  with 3 multi-sensor boxes are 1,500 Eur.
eHome in demo apartment Schwechat
Acknowledgements




Supported by: Austrian Federal Ministry for
   Transport, Innovation and Technology
    (FIT-IT contract number 815195).
Consortium: TU Vienna, Ceit Raltec, Kapsch
  Carriercom and Treventus Mechatronics.

  For questions: subasi@igw.tuwien.ac.at
  Web site: www.aat.tuwien.ac.at/ehome/

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4 subasi ehome-ifa-prague-v03 short

  • 1. Experiences from Assessing Daily Activities to Increase Safety and Comfort of Older Persons Living Alone Paul Panek, Peter Mayer, Özge Subasi and Wolfgang L. Zagler Institute for Design and Assessment of Technology Vienna University of Technology IFA 11th Global Conference on Ageing 28 May – 1 June 2012, Prague, Czech Republic
  • 2. Content  Introduction and Aim  Approach  Results from Fieldtrials  Conclusion
  • 3. Introduction & Aim  Many research papers available about AAL systems and activity monitoring – But unclear, to what extent such systems can be applied in real life  Therefore - Aim of eHome project: – Demonstration of practical usefulness – In daily use – Basic system with ZigBee based sensors was developed
  • 4. Approach  Daily life follows certain schedules – Given by routine – Following social and biological rhythms  eHome monitors continuously – Assessing activities in fixed time slices (e.g. 1 hour) – Triggering supportive or emergency actions if significant deviations – Keeps private data protected inside the user’s home  Objective of eHome: Improving safety and comfort of older persons living alone at home
  • 5. Approach  eHome system uses – Sensors connected via ZigBee – Storing data in a database – Data being processed in a small central unit – Situated at user’s home ( privacy of data) – Connected to the Internet.
  • 6. Approach  Event triggered expert system can raise alerts based on: – Time of activities (e.g. rising from bed compared to daily history) – Duration of selected activities (e.g. nightly leaving of bed) – Frequency of activities (e.g. reduction in cooking, hygiene)
  • 7. Approach  Assumption of eHome is: – Even by applying a rather coarse monitoring by a small set of sensors a sufficient insight into the user’s activity can be reached – Even if “better” and “more” sensors would be possible this was avoided in order to  Increase perspective for economic exploitation  Improve the to-be-expected user acceptance
  • 8. Field Trials  Extensive evaluation with – 5 research prototype systems – installed in 11 homes of older persons – over a total time of 18 months
  • 9. Field Trials  ZigBee Sensors for – Door / window – Acceleration & floor vibration (e.g. for fall detection) – Temperature – Cooking plate temp. (infrared) – Movement (passive infrared) – Light
  • 10. Impressions from Field Trials  Local User Interface – Touch-Screen Terminal without typical PC look – Fits to furniture – Easy to use – Video telephone – Smart-Home Controls – Emergency Call – Internet Browser
  • 11. e-HOME – reminders & call for help
  • 12. e-HOME – easy to use (video) phone
  • 14. Results  System was able to classify “usual behaviour” over time. This can be used in different ways: – Unusual sudden changes (e.g. not leaving bed in the morning)  triggering alarm – mid-term and long-term trends  present changes to care persons to let them judge about the meaning and severity of recognised changes.
  • 15. Presence in living room 9 July
  • 16. Results  The system is able to learn / adapt over time its threshold parameters  Remark: Even right from the beginning the system is able to work with initial values  important for practical use!  By adapting over time it will improve performance
  • 17. Conclusion  Despite needs for improvement there is evidence that the system actually is considered by users and experts to have the potential to bring significant benefits in supporting older persons and carers.  eHome prototype currently is used in LLM (CIP) and KSERA (FP7) project  Costs for low quantities of basic eHome system with 3 multi-sensor boxes are 1,500 Eur.
  • 18. eHome in demo apartment Schwechat
  • 19. Acknowledgements Supported by: Austrian Federal Ministry for Transport, Innovation and Technology (FIT-IT contract number 815195). Consortium: TU Vienna, Ceit Raltec, Kapsch Carriercom and Treventus Mechatronics. For questions: subasi@igw.tuwien.ac.at Web site: www.aat.tuwien.ac.at/ehome/