The document discusses a sensor-based telemonitoring system designed to assist elderly and disabled individuals in living independently at home. It outlines the system's capabilities in monitoring health and activity, including emergency detection and quality-of-life assessments, as well as its implementation in two EU projects: Saapho and Backhome. The evaluation results demonstrate the system's effectiveness in enhancing user safety and overall well-being.

1. AI-AM / NetMed 2015
4th International Workshop
on Artificial Intelligence
and Assistive Medicine
June 20, 2015
Monitoring People that Need
Assistance through a
Sensor-based System:
Evaluation and First Results
Xavier Rafael-Palou, Eloisa Vargiu, Felip Miralles
EURECAT
Barcelona, Spain

2. 1. Assisting elderly and disabled people
2. A sensor-based telemonitoring system
3. Evaluation and Results
4. The SAAPHO project
5. The BackHome project
6. Conclusions
2
Outline

3. 3
Assisting elderly and disabled people

4. How to better live alone at home…
4
People need to be independent to live better
Elderly people feel more safe living at their home
People need to return to their previous life roles
The long term rehabilitation goal for individuals with an TBI is resettlement back in the
community away from institutional care
IT IS URGENT TO ASSIST PEOPLE LIVING ALONE THROUGH ICT SOLUTIONS

5. 5
A Sensor-based Telemonitoring System

6. 6

7. 7
Home
4 in 1:
Door
Motion
Temperature
Luminosity
3 in 1:
Motion
Temperature
Luminosity
z-wave
smartphone
Raspberry pi

8. 8
Healthcare Center
 SC: Summary of a day

9. 9
Intelligent Monitoring

10. 10
Intelligent Monitoring
 PP
 Its goal is to preprocess the data iteratively sending a chunk
c to both ED and RE according to a sliding window
approach
 Starting from the overall data streaming, the system
sequentially considers a range of time |ti - ti+1| between a
sensor measure si at time ti and the subsequent measure
si+1 at time ti+1
 The output of PP is a window c from ts to ta, where ts is the
starting time of a given period and ta is the actual time

11. 11
Intelligent Monitoring
 ED
 It aims to detect and inform about emergency situations for
the end-users and about sensor-based system critical
failures
 Regarding the critical situations for the end-users, simple
rules are defined and implemented to raise an emergency,
when specific values appear on c
 Regarding the system failures, ED is able to detect
whenever user’s home is disconnected from the middleware
as well as when a malfunctioning of a sensor occurs
 Each emergency is a pair <si; lei> composed of the sensor
measure si and the corresponding label lei that indicates the
corresponding emergency

12. 12
Intelligent Monitoring
 AR
 Its goal is to recognize
activities performed by the
user
 To recognize if the user is at
home or away and if s/he is
alone, we implemented a
solution based on machine
learning techniques
 The output is a triple <ts;
te; l>

13. 13
Intelligent Monitoring
 EN
 It is able to detect events to be notified
 Each event is defined by a pair <ti; l> corresponding to the
time ti in which the event happens together with a label l
that indicates the kind of event
 Currently, this module is able to detect the following events:
o leaving the home
o going back to home
o receiving a visit
o remaining alone after a visit
o going to the bathroom
o going out of the bathroom
o going to sleep
o awaking from sleep

14. 14
Intelligent Monitoring
 SC
 Once all the activities and events have been classified,
measures aimed at representing the summary of the user’s
monitoring during a given period are performed
 Two kinds of summary are provided
o Historical
o Actual
 A QoL assessment system is also provided to assess a
specific QoL items
o Mobility
o Sleeping
o Mood

15. 15
Evaluation and Results

16. 16
Evaluation
 An abled-body woman who lives alone
 a window of 4 months for training and evaluation (training
dataset)
 a window of 1 month for the test (testing dataset)
 experiments have been performed on AR and EN

17. 17
Evaluation
 AR: Overall hierarchical approach

18. 18
Evaluation
 AR: Overall hierarchical approach

19. 19
Evaluation
 AR: Overall hierarchical approach

20. 20
Evaluation
 AR: Activity

21. 21
Evaluation
 AR: Location

22. 22
Evaluation
 AR: Indoor position

23. 23
Evaluation
 AR: Sleeping

24. 24
The SAAPHO project
AAL-2010-3-035

25. The Project
25
 SAAPHO was aimed at supporting Active Ageing by assisting
seniors to participate in the self-serve society preserving and
enhancing independence and dignity through the application of
innovative ICT-based solutions
Safety Health Social

26. 26
The BackHome project
FP7/2007-2013

27. The Project
27
 BackHome is the first European research project aimed at
delivering the ambitious, but critical, step to bring BNCI
systems to mainstream markets
The Objectives
 To study the transition from the hospital
to the home
 To learn how different BNCIs and other
assistive technologies work together
 To reduce the cost and hassle of the
transition from the hospital to the home

28. 28
Conclusions

29.  The proposed solution provides
 An no-intrusive sensor-based system installed at user’s
home
 An intelligent system that mines data to study habits and
quality-of-life of monitored users
 A web application for therapists and caregivers to stay
aware about the user status, condition, habits and quality-of-
life
 The overall system is part of the SAAPHO and BackHome EU
projects
29
Closing Remarks

30. eloisa.vargiu@eurecat.org