PROJECT SUMMARY/ABSTRACT
Laband real-world validation of a system for monitoring ingestive behavior
Project Summary:
Population-based and short-term laboratory findings demonstrate eating behaviors linked to overeating and
excess body weight can be modified to reduce energy intake and enhance satiety. These findings suggest that
slowing specific ingestive behaviors (IB; bites, chews, oral processing) may thus be effective for healthy body
weight management. However, no accurate automated methodology exists to measure these combined IB
outside laboratories, in people's free-living, real-world settings. Thus, the central goal of the proposed project
is to validate and test a wearable device assembly pairing two validated instruments that can provide these
measurements with good accuracy and low participant burden. One is a wrist-worn bite counter, which detects
the wrist-roll motion associated with placing food in the mouth, tracking bite number and bites per minute for
each eating episode. The other is a discreet chewing sensor adhered to the skin over the condyle bone, to
detect chewing frequency and duration, as well as oral processing. Combined, these sensors can provide data
on chew-to-bite ratio (which has implications in energy intake and satiety) and can capture overall eating
episodes and IB with more precision than a single device alone. The project includes laboratory aims,
supported by two studies for device assembly validation across a range of foods, beverages, utensils and
eating styles, along with real-world aims, supported by three studies that progress from semi-controlled to true
free-living settings in people's everyday lives. These will include restaurants, cafeterias, work, school, and
home lives. Device assembly data will be compared to multiple established ground truth measures such as
video, the universal eating monitor, observation, and self-reports. Participants will represent a broad range of
body mass index, adult ages, genders, and race/ethnicity, with over-representation from LatinX communities,
who experience higher incidence of obesity and associated health conditions. Our multi-disciplinary team
includes a nutritionist specializing in eating behaviors associated with obesity, a psychologist specializing in
behavior monitoring through wearable technologies and longitudinal analysis, and a computer engineer
specializing in wearable devices to detect IB. Scientific
automated
impacts f this project lie in developing a tool to enable
long-term free-living data collection on behaviors vital for weight management.
o
Health impacts lie in
potentially equipping people with a passive self-monitoring tool for improving eating behaviors and diet, with
minimal participant burden, yet optimizing impact through targeting key IB. Thus, promising multi-disciplinary
laboratory findings will be moved to free-living settings with a user-friendly non-invasive digital device
assembly, allowing for self-monitoring. The
management
ultimate goal is t o facilitate evidence-based personalized weight
programs leveraging real-world modification of eating behavior that are scalable to large
populations.