1. From Smart Home to Smart Care : Pervasive Assistance for Cognitively Impaired People Sylvain Giroux

2. Plan Context Objectives and Approach Pervasive and mobile computing, Tangible User interface From homes… Hardware level: networks, sensors, effectors … to smart homes … Middleware level: pervasive infrastructure … to smart care ! Application level: cognitive assistance & tele-monitoring Validation Clinical studies Conclusion

3. Context People suffering of cognitive impairments in Quebec Alzheimer disease : 5.1% of people over 65 years old Head trauma : 3000 new cases each year Schizophrenia : 1% of the population In many cases, they would be able to stay at home if light assistance was provided. But healthcare resources are scarce. So relatives have to take responsibility for care. It then turns to an exhausting burden. Hence relatives and caregivers urge for help.

4. Objectives Provide adapted and personalized environmental cues to Foster the autonomy of cognitively impaired people Reduce risks and hazards Pervasive computing & Tangible user interfaces Keep ensuring continuous cognitive assistance outside people’s home Mobile computing & Location-based services Help relatives and caregivers to stay in touch at distance with cognitively impaired people

5. From homes… Smart homes are augmented environments Heterogeneous networks Sensors networks Embedded processors in devices, clothes, jewels… Information appliances Networked communicating objects

6. DOMUS: an augmented apartment

7. … smart homes … Smart homes are augmented environments Heterogeneous networks Wireless : WiFi, Bluetooth, RFID, UWB... Wired : Ethernet, Electrical wires, X10, power line… Servers Full control over sounds and video streams

8. … smart homes … Smart homes are augmented environments Sensors networks Identification and localization of objects and people Ubisense tags, UWB Smart tags (RFID)

9. … smart homes … Smart homes are augmented environments Embedded processors in devices and clothes Not yet investigated

10. … smart homes … Smart homes are augmented environments Information appliances Fixed: smart boards, Icebox… Mobile: laptop, wireless screen, PDAs…

11. … smart homes … Smart homes are augmented environments Networked communicating objects Sight Hearing Smell (not yet investigated) Touch (not yet investigated) Taste (is it possible ?)

12. From homes to smart homes

13. Towards a pervasive infrastructure Some issues investigated at DOMUS Spontaneous networking Heterogeneous networks Autonomic computing Mobile code and agents Location and context awareness Security and privacy Some prototypes A pervasive reminder system Multi-channel delivery of services

14. A Pervasive Reminder System for Smart Homes How to localize a user from simple sensors information ? How to achieve pervasiveness? Follow-me : transparent user friendly migration of sessions How to use spontaneous networking and service discovery to build zero-configuration system ? How to cope with heterogeneity of devices, networks, and OS ? How to keep the system in a clean state ?

15. Multi-channel delivery of services On-the-fly generation of user interfaces from raw code Means to control complex interactions with a user Ready to use service delivery infrastructure

16. … to smart care Smart homes can assist cognitively impaired people foster their autonomy. The whole home becomes a true cognitive prosthesis. As well, smart homes can help caregivers to grant better care give a sense of security to residents and their relatives

17. Cognitive assistance What is the available information ? Identification and location of people and objects Objects involved in an activity Primitive actions Who the user is ? personalization What is the user doing ? Activity recognition Hierarchical models Lattice-theory How to assist the user? Highligth objects Tangible user interfaces

18. Activity recognition Based on plan recognition Hierarchical Markov models Lattice-based models Based on involved objects Perkowitz et al., Mining Models of Human Activities from the Web, WWW 2004, May 17-22, 2004, New York, NY USA.

19. Personalization Every person is different Cognitive modelling exploiting episodic memory To know from life habits, how one usually performs an activity method usually used to achieve a task estimations on time (averge time of completion…) most likely location

20. Cognitive deficits Deficits addressed Initiation Memory Planning Attention

21. Initiation deficits Initiation deficits leads to inactive periods whereas the person is supposed to perform actions Wandering for a long time could be attributed to an initiation deficit >> Prompt the resident

22. Memory deficits Difficulties to remember the activity to perform the steps of the activity the locations of the tools and materials involved in that activity. >> Show-me objects + « Follow-me » applied to objects The lamp turns off when the object is too far away. The lamp turns on to highlight the searched red book

23. Planning deficits Difficulties to perform an appropriate sequence of actions in the rightorder to achieve a goal. >> Prepare_coffee = {take_milk, take_cup…} >> Show to the user where to perform the next action

24. Attention deficits Shifts of attention from the activity under progress to a stimulus causing interference The current activity may be forgotten and never completed >> Remind the activity under progress to the resident

25. Validation Clinical studies using prototypes are in preparation and will soon be on-going at Fernand-Séguin research center, L-H Lafontaine Hospital, Montreal Dr Emmanuel Stip, psychiatrist Schizophrenia Centre de Réadaptation Estrie, Sherbrooke Head trauma

26. Conclusion Pervasive computing and tangible user interfaces can help to transform home into smart homes adapted to cognitively impaired people Going beyond the usual view of computing as “PC-based” Pervasive computing enables a seamless integration of assistance in residents’ everyday life Going beyond traditional human computer interfaces TUI helps to turn the whole house into a cognitive prosthesis Such smart homes can Foster people’s autonomy Lead to smarter care

27. Our team Researchers from the Faculties of science, engineering, and administration Sylvain Giroux, Ph. D. in Computer science Hélène Pigot, Ph. D. in Computer science and B. in occupational therapy André Mayers, Ph. D. in Computer science and M. inpsychology Philippe Mabilleau, Ph.D. in engineering Claude Caron (geo-business) Analyst Francis Bouchard Students 6 Ph. D. students 12 M. Sc. students 6 B.Sc. students, 2 international trainees (M. Sc. level) Some collaborations CRE, Centre de réadaptation Estrie Centre de recherches Fernand Séguin, Computer science Université Joseph Fourier, Grenoble France Telecom Ariane Controls, Canada

28. Thank you for your attention http://domus.usherbrooke.ca/