1 / 19

Modeling of ADLs in its Environment for Cognitive Assistance

Modeling of ADLs in its Environment for Cognitive Assistance . Jérémy Bauchet and André Mayers. Introduction. Cognitive assistance, in smart homes, aims at supporting occupants for the completion of their activities of daily living (ADLs). Introduction (2).

gilon
Télécharger la présentation

Modeling of ADLs in its Environment for Cognitive Assistance

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Modeling of ADLs in its Environment for Cognitive Assistance Jérémy Bauchet and André Mayers

  2. Introduction • Cognitive assistance, in smart homes, aims at supporting occupants for the completion of their activities of daily living (ADLs)

  3. Introduction (2) • Implies for the system a prior knowledge about the occupant • its activities • its environment • This knowledge is necessary for : • activity recognition, as a prior step of cognitive assistance in smart homes • finally, for cognitive assistance

  4. Plan • Introduction • A model for the description of ADLs • a hierarchical approach • the environment of completion • Taking into account the specific behavior of the occupant • Implementation of the models • Results and perspectives concerning activity recognition and cognitive assistance • Conclusion

  5. A hierarchical model for ADLs description • Two type of nodes : tasks and methods • a task : a goal • a method : a way to realize the task → a set of subtasks → and rules of integration of subtasks : • partial or total sequence • repetition or necessity constraint

  6. A hierarchical model for ADLs description (2) • Roots are abstract tasks (ADLs, IADLs) • Leaves are methods of terminal tasks = an atomic way to realise a concrete goal • Tasks can be common to several methods → if common nodes are duplicate, this model is a tree

  7. Model of activity

  8. A model of ADLsin its environment • Environment of activity completion • Includes all actors of activity completion • daily living objects • furniture • the occupant, as the actor of his own task completion → e.g. : her/his current position

  9. Description of the environmentof completion • Static description : • Actors : fridge • Events concerning actors fridge : door opened, door closed • Dynamic description : Assertions, giving current value of several pieces of information concerning actors • <fridge, door, opened> • <occupant, position, kitchen>

  10. Links between activities andthe environment • Events concerning actors in the environment are associated with terminal methods • events are a consequence of the concrete actions of the occupant • events can be observed via distributed sensors • occurrence of events are used for activity recognition

  11. Links between activities andthe environment (2) • Tasks and method are considered as operators of a planning domain • they have preconditions and effects • both concern the environment

  12. Taking into account the specific behavior of the occupant • The activity model is a support for the generic description of ADLs and IADLs → We need an occupant model to describe his/her specific comportment

  13. An episodic memory for the occupant model • Allows to precise how one occupant usually completes an activity • the method used for a given task • the time slot of completion • the location • the sequence of subtasks

  14. Implementation • XML • library of tasks and methods (activity model) • description of the environment • episodic memory persistence • SVG • graphical representation of the environment • Java • XML parsing • internal representation of the models and treatments • SVG management

  15. Results and perspectives : Concerning activity recognition • Goal : to compute the probability of completion of (I)ADLs given inputs • Inputs are : • description of ADLs • events • current time • knowledge about the occupant habits of life, given by the episodic memory

  16. Activity recognition

  17. Results and perspectives (3) :Concerning cognitive assistance • Description of activities, for step by step or global assistance • Preconditions → what has to be done before, where the activity can take place • Rules of integration for subtasks → how to complete correctly the activity • Episodic memory → anticipation process

  18. Conclusion

More Related