Joseph Modayil, Rich Levinson, Craig Harman, David Halper, Henry Kautz. 2008.
Integrating sensing and cueing for more effective activity reminders.
AAAI Fall Symposium on AI in Eldercare (FS-08-02) ,
Abstract We are investigating how sensors can improve a
portable reminder system (PEAT) that helps individuals accomplish
their daily routines. PEAT is designed for individuals who have
difficulty remembering when to perform activities because of cognitive
impairments from strokes or other brain injuries. These impairments
can cause a significantly reduced quality of life for afflicted
individuals and their caregivers. PEAT provides assistance by
planning a schedule of activities for a user, and by cueing the user
when activities should begin or end. One limitation of PEAT is that
it requires the user to manually indicate when an activity starts or
stops, which causes unnecessary cues for a user who needs only
occasional reminders. By incorporating feedback from reliable
sensors, the software can automatically infer which activity the user
is performing. With this information, we expect that PEAT will be
able to cue the user more effectively, by not cueing the user when
sensors indicate that activities have already started or stopped, and
by providing compliance cues that rem ind the user when steps of an
activity have been forgotten. We present a description of the system,
implemented scenarios, and a discussion of potential benefits and
pitfalls with this approach.