This document summarizes a sensor-based telemonitoring and home support system called TMHSS that aims to improve the quality of life for people with disabilities. The TMHSS uses ambient intelligence technologies, automatic quality of life assessments, and brain-computer interfaces to provide remote monitoring, cognitive rehabilitation, and support for physical and social autonomy at home. A case study of the system involves its implementation for brain-computer interface users in the BackHome project. The system architecture integrates various sensors and smart home devices to remotely collect health data and enable independent living. Future work involves additional testing of the system at users' homes and analyzing the results to validate its ability to assess and support quality of life.

1. AAATE 2013
20th September 2013
A Sensor-based Telemonitoring and Home
Support System to Improve Quality of Life
through BNCI
Eloisa Vargiu, Juan Manuel Fernández,
Sergi Torrellas, Stefan Dauwalder,
Marc Solà, and Felip Miralles

2. The Aim of the Work
 WHAT: To improve Quality of Life
2
 HOW: Telemonitoring and Home Support
 WHO: BNCI Users
 WHERE: BackHome Project

3. Telemonitoring
&
Home Support

4. 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 4

5. Our Approach
Care
Center
HomeUser Social
Environment
TMHSS
Contexts
5

6. Our Approach
Care
Center
HomeUser Social
Environment
TMHSS
Functionalities
Personal
Autonomy
Cognitive
Rehabilitation
Social
Autonomy
Remote
monitoring
QoL Assessment
6

7. Our 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
7

8. The TMHSS at a Glance
8

9. 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
9

10. The TMHSS
 Physical autonomy (smart home control)
 To control a TV
 To turn/off a device
 To control a IP camera
 Social autonomy (social networking)
 To communicate with the therapists
 To communicate with relatives
 To communicate with friends
 Personalization
 To adapt to users’ habits
 To adapt to the environment 10

11. The TMHSS
11

12. The TMHSS
 Therapists can
 plan future patient activities
 personalize exercises and
activities
 Users can
 perform cognitive rehabilitation tasks
 perform cognitive activities
 receive a feedback on the performed
activities
12

13. The TMHSS
 To 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
Validation
13

14. The Challenge

15. To Improve Users’ Quality of Life!
15

16. The Challenge
 From
 a Visual Analogue
Scale questionnaire…
 To
 automatic assessment
through the TMHSS
16

17. The Challenge
17

18. Case Study

19. Case Study
 BNCI users
 BackHome project
19

20. 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 20

21. Where We Are

22. TMHSS Architecture
22
AmI Block
Service
Manager
Communication
Manager
Context
Awarenes
s Module
User Interface
BCI Module
Proactive Reasoning Engine
Quality of
Life
Module
BCI Block
Internet
Smart Home
Communication
Cognitive
Rehabilitation
Services and Applications
Cognitive
Rehabilitation
Module
User
Telemonitoring
Quality of Life
Module
Therapist Station
22
UserStation

23. QoL Assessment
23
 Mood
 First experiments on social mining on Twitter data
 Study of social mining on FB
 Mobility
 Definition of the sensor network
 Identification of the needed sensors
 Usual Activities
 Control over home environment
 Leisure activities
 Study of successes and failures of user’s interactions with
the system

24. Where We Are Going

25. To-Do List
 To install the 2nd prototype of the system at end-
users’ facilities (Belfast and Wurzbürg)
 To start experiments with end-users at home
 Data analysis of the data provided by the first
testing phase
 Comparisons of obtained results with
those given by the users filling the
VAS questionnaire
25

26. Conclusions

27. Conclusions
 Supporting people with disabilities is an
important task
 Telemonitoring and home support to remotely
assist both therapists and disabled people
 suitable sensors
 physical and social support
 Improvement of quality of life of people
27

28. 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
28

29. Thanks for your
attention!
evargiu@bdigital.org