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ICAART 2013
15th February 2013
Eloisa Vargiu
Barcelona Digital
Technology Center
User Profiling of
People with Disabilities
A joint work with:
Luigi Ceccaroni, Laia Subirats, Suzanne Martin and Felip Miralles
Outline of the talk
 BackHome Project
 Telemonitoring and Home Support in
BackHome
 The Challenge: Automated Assessment of
Quality of Life
 Conclusions & Future Work
2
3
 … BackHome Project
Aim & Motivation
 The long term rehabilitation goal for
individuals with an acquired brain
injury is resettlement back in the
community away from institutional
care
 The ideal scenario is that the
person will return to her/his
previous home and life roles
Aim & Motivation
 In the early post-discharge phase, additional
home care is provided to support the
individual and their family
 Unfortunately, the provided support is often
not long enough to achieve the maximum
possible independence
 The transition to the home is often very
difficult and traumatic for the individual and the
carers
BackHome Main Goal
 To assist people with disabilities back home
after a discharge(*)
(*) Daly, J., Armstrong, E., Miralles, F., Vargiu, E., Müller-Putz, G., Hintermller, C., Guger,
C., Kübler, A., and Martin, S. (2012). BackHome: Brain-neural-computer interfaces on
track to home. In RAatE 2012 -Recent Advances in Assistive Technology &Engineering.
BackHome Objectives
 To study the transition from the hospital to
the home
 To learn how different BNCIs and other
assistive technologies work together
 To learn how different BNCIs and
other assistive technologies can help in the
transition from the hospital to the home
 To reduce the cost and hassle of the transition
from the hospital to the home
A Reference Scenario
 Chara is a painter in her thirties
 About eight years ago she started to have difficulties
holding her paint brush
 She was diagnosed with amyotrophic lateral sclerosis
and became tetraplegic and artificially ventilated
 She was so depressed that she refused treatment
when diagnosed with pneumonia
 She survived and just recently had her first session
with BNCI-based Brain Painting(*)
(*) Münssinger, J., Halder, S., Kleih, S., Furdea, A., Raco, V., H¨ osle, A., andK ¨ ubler, A.
(2010). Brain painting: First evaluation of a new BCI application with ALS-patients and
healthy volunteers. Front Neurosci, 4:182.
9
 … telemonitoring and home
support in BackHome
Vargiu, E., Miralles, F., Martin, S., and Markey, D. (2012).
BackHome: Assisting and telemonitoring people with
disabilities. In RAatE 2012 - Recent Advances in As-sistive Technology & Engineering.
Telemonitoring & Home Support
 Telemonitoring & Home Support Systems
(TMHSSs) provide a range of services which
enable patients to transition more smoothly
into the home environment and be maintained
for longer at home
 TMHSSs
 Facilitate services which are convenient for patients,
avoiding travel whilst supporting participation in basic
healthcare
 Can be a cost effective intervention which
promotes personal empowerment
The BackHome Approach
Care
Center
HomeUser Social
Environment
TMHSS
Contexts
The BackHome Approach
Care
Center
HomeUser Social
Environment
TMHSS
Functionalities
Personal
Autonomy
Cognitive
Rehabilitation
Social
Autonomy
Remote
monitoring
QoL Assessment
The BackHome Approach
Care
Center
HomeUser Social
Environment
TMHSS
Personal
Autonomy
Cognitive
Rehabilitation
Social
Autonomy
Remote
monitoring
QoL Assessment
Technologies
Ambient Intelligence
Automatic
Quality of Life
Assessment
SystemRemote Cognitive
Rehabilitation
Brain Neural
Computer
Interface
Complementary
Interfaces
The TMHSS
Smart-Nodes
GAS
Temperature
Wearable
Sensors
Gyro
ECG
EMG
Smart-objects
Twitter
Toys
AmI
AmI is the “glue” technology
providing the intelligent baseline framework
Robot
The TMHSS
 Physical autonomy (smart home control)
 To turn on/off a TV
 To open/close a curtain
 To set the room temperature
 Social autonomy (social networking)
 To communicate with the therapists
 To communicate with relatives
 To communicate with friends
The TMHSS
 Performing cognitive activities through
 a communication system
• to plan future patient activities
• to personalize exercises and activities
 sensors-based technologies
• to monitor exercise execution and performance
• to perform cognitive activities (e.g., Brain Painting)
 smart objects
• to perform cognitive rehabilitation task (e.g., with a
robot)
The TMHSS
The TMHSS
 QoL is the subjective experiences or
preferences expressed by an individual in
relation to specified aspects of her/his life, with
a particular reference to the health status
The TMHSS
 The QoL assessment system will help answer
basic questions about the state of the user,
such as
 “is she depressed?”
 “has she decreased her activity level?”
 “is she more engaged in social interactions?”
BackHome
Heterogeneous
information collected by
the system
User
health status
20
 … The Challenge
Automated Assessment of
Quality of Life
QoL Assement as User Profiling
 The idea
 A relevant part of the profile of people with health
diseases is their QoL
 How to assess QoL
 Several questionnaires have been proposed and
adopted
 The user is asked to answer to a predefined set of
questions about her/his mental and
psychological status and feeling
The Challenge
 Open Issue
 It could become boring and annoying for a user to
answer to them, especially if they are asked to do
that very frequently
 Our Proposal
 Automated assessment of QoL
The Adopted Questionnaire
 EQ-5D(*)
 A standardized measure of health status
 Provides a simple, generic measure of health for
clinical and economic appraisal
 Provides a simple descriptive profile and a single
index value for health status that can be used in the
clinical and economic evaluation of health care as
well as in population health surveys
(*) The Euroqol Group (1990). Euroqol a facility for the measurement of health-related
quality of life. Health Policy, 16:199–208.
The Adopted Questionnaire
The Adopted Questionnaire
Geyh, S., Cieza, A., Kollerits, B., Grimby, G., and Stucki, G. (2007). Content comparison
of health-related quality of life measures used in stroke based on the international
classification of functioning, disability and health (ICF): a systematic review. Quality of
Life Research, 16(5):833–851.
Pervasive QoL Assessment
 Mobility
 through location sensors
Pervasive QoL Assessment
 Self-care
 in principle, also self-care
activities can be monitored
by relying on suitable
sensors
 for privacy issues, we
decided to not monitor such
activities
Pervasive QoL Assessment
 Usual Activities (housework,
education and/or leisure
activities)
 through the BNCI system
 Usual Activities (family and
friends relationships)
 through the support of
communication system
 through the support of social
network
Pervasive QoL Assessment
 Pain/Discomfort
 through text mining
algorithms applied on social
networking and
communication activities
Pervasive QoL Assessment
 Anxiety/Depression
 through the BNCI system
(fatigue, spasticity, stress)
 through text mining
algorithms applied on social
networking and
communication activities
Pervasive QoL Assessment
 Health state
 by performing inference on
all the data gathered by the
BNCI system, the wearable
sensors and the social
communications
32
 … Conclusions & Future
Work
Conclusions
 Profiling people with functional diversity
 QoL assessment
 BackHome challenge
 Pervasively assessing the QoL automatically
 Preliminary proposal
 A smart home healthcare monitoring system
 EQ-5D questionnaire
Work in Progress
 Definition of an ad-hoc BackHome questionnaire
 Visual Analogue Scale (VAS) questionnaire
 First prototype installation and testing
 Cedar Foundation (U.K.)
 Univ. of Würzburg (Germany)
Future Work
 Data analysis of the data provided by the first
testing phase
 Selection of wearable sensors according to user
requirements
Acknowledgements
 BackHome
 Website: www.Backhome-FP7.eu
 The research leading to these results has received
funding from the European Community's, Seventh
Framework Programme FP7/2007-2013,
BackHome project grant agreement n° 288566
 Consortium
Thanks for your
attention!
37
evargiu@bdigital.org

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BackHome

  • 1. 1 ICAART 2013 15th February 2013 Eloisa Vargiu Barcelona Digital Technology Center User Profiling of People with Disabilities A joint work with: Luigi Ceccaroni, Laia Subirats, Suzanne Martin and Felip Miralles
  • 2. Outline of the talk  BackHome Project  Telemonitoring and Home Support in BackHome  The Challenge: Automated Assessment of Quality of Life  Conclusions & Future Work 2
  • 4. Aim & Motivation  The long term rehabilitation goal for individuals with an acquired brain injury is resettlement back in the community away from institutional care  The ideal scenario is that the person will return to her/his previous home and life roles
  • 5. Aim & Motivation  In the early post-discharge phase, additional home care is provided to support the individual and their family  Unfortunately, the provided support is often not long enough to achieve the maximum possible independence  The transition to the home is often very difficult and traumatic for the individual and the carers
  • 6. BackHome Main Goal  To assist people with disabilities back home after a discharge(*) (*) Daly, J., Armstrong, E., Miralles, F., Vargiu, E., Müller-Putz, G., Hintermller, C., Guger, C., Kübler, A., and Martin, S. (2012). BackHome: Brain-neural-computer interfaces on track to home. In RAatE 2012 -Recent Advances in Assistive Technology &Engineering.
  • 7. BackHome Objectives  To study the transition from the hospital to the home  To learn how different BNCIs and other assistive technologies work together  To learn how different BNCIs and other assistive technologies can help in the transition from the hospital to the home  To reduce the cost and hassle of the transition from the hospital to the home
  • 8. A Reference Scenario  Chara is a painter in her thirties  About eight years ago she started to have difficulties holding her paint brush  She was diagnosed with amyotrophic lateral sclerosis and became tetraplegic and artificially ventilated  She was so depressed that she refused treatment when diagnosed with pneumonia  She survived and just recently had her first session with BNCI-based Brain Painting(*) (*) Münssinger, J., Halder, S., Kleih, S., Furdea, A., Raco, V., H¨ osle, A., andK ¨ ubler, A. (2010). Brain painting: First evaluation of a new BCI application with ALS-patients and healthy volunteers. Front Neurosci, 4:182.
  • 9. 9  … telemonitoring and home support in BackHome Vargiu, E., Miralles, F., Martin, S., and Markey, D. (2012). BackHome: Assisting and telemonitoring people with disabilities. In RAatE 2012 - Recent Advances in As-sistive Technology & Engineering.
  • 10. Telemonitoring & Home Support  Telemonitoring & Home Support Systems (TMHSSs) provide a range of services which enable patients to transition more smoothly into the home environment and be maintained for longer at home  TMHSSs  Facilitate services which are convenient for patients, avoiding travel whilst supporting participation in basic healthcare  Can be a cost effective intervention which promotes personal empowerment
  • 11. The BackHome Approach Care Center HomeUser Social Environment TMHSS Contexts
  • 12. The BackHome Approach Care Center HomeUser Social Environment TMHSS Functionalities Personal Autonomy Cognitive Rehabilitation Social Autonomy Remote monitoring QoL Assessment
  • 13. The BackHome Approach Care Center HomeUser Social Environment TMHSS Personal Autonomy Cognitive Rehabilitation Social Autonomy Remote monitoring QoL Assessment Technologies Ambient Intelligence Automatic Quality of Life Assessment SystemRemote Cognitive Rehabilitation Brain Neural Computer Interface Complementary Interfaces
  • 14. The TMHSS Smart-Nodes GAS Temperature Wearable Sensors Gyro ECG EMG Smart-objects Twitter Toys AmI AmI is the “glue” technology providing the intelligent baseline framework Robot
  • 15. The TMHSS  Physical autonomy (smart home control)  To turn on/off a TV  To open/close a curtain  To set the room temperature  Social autonomy (social networking)  To communicate with the therapists  To communicate with relatives  To communicate with friends
  • 16. The TMHSS  Performing cognitive activities through  a communication system • to plan future patient activities • to personalize exercises and activities  sensors-based technologies • to monitor exercise execution and performance • to perform cognitive activities (e.g., Brain Painting)  smart objects • to perform cognitive rehabilitation task (e.g., with a robot)
  • 18. The TMHSS  QoL is the subjective experiences or preferences expressed by an individual in relation to specified aspects of her/his life, with a particular reference to the health status
  • 19. The TMHSS  The QoL assessment system will help answer basic questions about the state of the user, such as  “is she depressed?”  “has she decreased her activity level?”  “is she more engaged in social interactions?” BackHome Heterogeneous information collected by the system User health status
  • 20. 20  … The Challenge Automated Assessment of Quality of Life
  • 21. QoL Assement as User Profiling  The idea  A relevant part of the profile of people with health diseases is their QoL  How to assess QoL  Several questionnaires have been proposed and adopted  The user is asked to answer to a predefined set of questions about her/his mental and psychological status and feeling
  • 22. The Challenge  Open Issue  It could become boring and annoying for a user to answer to them, especially if they are asked to do that very frequently  Our Proposal  Automated assessment of QoL
  • 23. The Adopted Questionnaire  EQ-5D(*)  A standardized measure of health status  Provides a simple, generic measure of health for clinical and economic appraisal  Provides a simple descriptive profile and a single index value for health status that can be used in the clinical and economic evaluation of health care as well as in population health surveys (*) The Euroqol Group (1990). Euroqol a facility for the measurement of health-related quality of life. Health Policy, 16:199–208.
  • 25. The Adopted Questionnaire Geyh, S., Cieza, A., Kollerits, B., Grimby, G., and Stucki, G. (2007). Content comparison of health-related quality of life measures used in stroke based on the international classification of functioning, disability and health (ICF): a systematic review. Quality of Life Research, 16(5):833–851.
  • 26. Pervasive QoL Assessment  Mobility  through location sensors
  • 27. Pervasive QoL Assessment  Self-care  in principle, also self-care activities can be monitored by relying on suitable sensors  for privacy issues, we decided to not monitor such activities
  • 28. Pervasive QoL Assessment  Usual Activities (housework, education and/or leisure activities)  through the BNCI system  Usual Activities (family and friends relationships)  through the support of communication system  through the support of social network
  • 29. Pervasive QoL Assessment  Pain/Discomfort  through text mining algorithms applied on social networking and communication activities
  • 30. Pervasive QoL Assessment  Anxiety/Depression  through the BNCI system (fatigue, spasticity, stress)  through text mining algorithms applied on social networking and communication activities
  • 31. Pervasive QoL Assessment  Health state  by performing inference on all the data gathered by the BNCI system, the wearable sensors and the social communications
  • 32. 32  … Conclusions & Future Work
  • 33. Conclusions  Profiling people with functional diversity  QoL assessment  BackHome challenge  Pervasively assessing the QoL automatically  Preliminary proposal  A smart home healthcare monitoring system  EQ-5D questionnaire
  • 34. Work in Progress  Definition of an ad-hoc BackHome questionnaire  Visual Analogue Scale (VAS) questionnaire  First prototype installation and testing  Cedar Foundation (U.K.)  Univ. of Würzburg (Germany)
  • 35. Future Work  Data analysis of the data provided by the first testing phase  Selection of wearable sensors according to user requirements
  • 36. Acknowledgements  BackHome  Website: www.Backhome-FP7.eu  The research leading to these results has received funding from the European Community's, Seventh Framework Programme FP7/2007-2013, BackHome project grant agreement n° 288566  Consortium