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During testing, the device proved
remarkably effective. Older adults were able to complete
about 25 % more of the steps involved in hand washing on
their own, without a caregiver. In one case, the
caregiver actually spent less than 30 seconds with the
person – instead of the usual seven or eight minutes.
The researchers are now refining
and enhancing the system with visual prompts. They think
some users will benefit from seeing video reminders on a
screen.
In his busy office, Dr. Mihailidis
and his colleagues are also developing a separate system
to detect when someone falls at home. Using a
ceiling-mounted camera, the computer vision system
tracks a person’s movements in their home.
“If they do fall, the system
automatically detects this and calls for help,” says
Dr. Mihailidis. “This means that even if they are
unconscious or severely injured, they can still get
help.”
Working with Lifeline Systems
Canada, a provider of personal response and support
services, the researchers are now adding a feedback
feature. “When a fall is detected, the system would
ask the person: ‘Are you okay?’ Based on their
response or lack thereof, the system makes an
intelligent decision as to what level of help is
required.”
Down the road, the device could
also be used to monitor the amount of time a person
spends sleeping, or the number of visits to the
bathroom. It would alert a caregiver if the behaviour
did not fit with typical patterns.
Dr. Mihailidis stresses that the
cameras do not actually record anything. Hooked up to a
computer, all they “see” is moving blobs or
silhouettes.
Only a decade ago – when Dr.
Mihailidis started his Master’s degree – many people
thought artificial intelligence was too complicated to
be applied to such real-world problems.
“The computer power didn’t
really exist back then. Now, we can write stuff on a
standard PC without any problems,” observes Dr.
Mihailidis. Something else has changed too, he says.
There are now strong, collaborative connections between
theoretical computer scientists, biomedical engineers
and clinicians, he says.
Dr. Mihailidis believes his
research can eventually help us all in our daily lives.
“Right now, we’re developing systems for people with
moderate-to-severe dementia and for older adults, but in
the future this type of technology will
likely serve many people.”
Wouldn’t it be great to live in a
house that understands your habits and locates your
wallet or gloves for you as you rush out of the door in
the morning?
Says Dr. Mihailidis: “It would be
great if your house could say: “Your wallet’s
over there!” I often forget things and a reminder like
that would be really,
really helpful.”
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