Imagine a dining table that could sense foods and beverages being
consumed from its surface. The table could calculate statistics about
how a person eats including eating rate, bite size, portion consumed
and food-to-beverage ratio. All of these habits could be tracked over
time to help the user target behavior changes intended to reduce
consumption, such as slowing eating, reducing bite size, reducing
portion size, or increasing food-to-beverage ratio.
Detecting and measuring bites
The idea of a table that could monitor consumption was first envisioned
as something called the universal eating monitor (UEM) in 1980
(see left figure below).
It used an embedded scale to measure weight continuously over time as
someone ate at the table, calculating g/min consumed.
The method works well for detecting individual consumption events (bites)
when the user eats under carefully controlled conditions, including not
cutting or stirring foods on the table, waiting between bites, and excluding
drinks (see middle figure below).
We are researching methods that work during natural eating that produces
more complex weight signals (see right figure below).
UEM concept (1980)
Table weight sensed when eating is carefully controlled
Table weight sensed during natural, unrestricted eating