Objective Eating Measurement
Objective Eating Measurement - Related Videos
05:57
Fat Preference: A Novel Model of Eating Behavior in Rats
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Cited by 9 •
2014
Dietary fat content influences both energy intake and body fat composition in mammals. By examining rats’ preference for high fat food in a series of choice experiments, it is possible to test genetic differences and pharmacological interventions on their preference for high fat food.
01:23
Binge Eating Disorders
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2025
Binge eating disorder is a significant mental health condition characterized by recurrent episodes of excessive food consumption within a short period, accompanied by a perceived loss of control over eating behavior. Unlike occasional overeating, binge eating disorder is marked by distressing emotions such as guilt, shame, and anxiety following binge episodes. The disorder affects individuals across different ages and backgrounds, with profound implications for physical and psychological...
14:38
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
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Cited by 11 •
2012
We describe a novel methodology for creating naturalistic 3-D objects and object categories with precisely defined feature variations. We use simulations of the biological processes of morphogenesis and phylogenesis to create novel, naturalistic virtual 3-D objects and object categories that can then be rendered as visual images or haptic objects.
06:43
The Crossmodal Congruency Task as a Means to Obtain an Objective Behavioral Measure in the Rubber Hand Illusion Paradigm
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Cited by 21 •
2013
We demonstrate how an objective measure can be employed in the widely employed rubber hand illusion paradigm. This measure is obtained by modifying the well-established crossmodal congruency task. This task allows the investigation of multisensory processes which are critical for modulations of body representations as in the rubber hand illusion.
10:14
Object Substitution Masking
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Visual masking is a term used by perceptual scientists to refer to a wide range of phenomena in which in an image is presented but not perceived by an observer because of the presentation of a second image. There are several different kinds of masking, many of them relatively intuitive and unsurprising. But one surprising and important type of masking is called Object Substitution Masking. It has been a focus of research in vision...
FAQs
Memory-based reports can introduce interpretive uncertainty, whereas observable or instrument-recorded data document specific features of eating as they occur. Depending on the method, researchers can quantify foods consumed, portion sizes, meal timing, eating rate, bite frequency, or chewing. This distinction supports more precise behavioral analyses and improves estimates of energy intake when self-report alone may be insufficient.
The measurable features depend on the selected recording approach. Weighed records and photographs can characterize foods and portion sizes, while direct observation or video can document meal timing, eating rate, and bite frequency. Wearable sensors may assess chewing. Together, these measures allow researchers to examine not only what is eaten, but also how and when eating occurs.
Eating rate, bite frequency, and chewing provide behavioral detail that total intake alone cannot show. Measuring these features can reveal differences in the pace and structure of meals and help identify patterns associated with appetite, obesity, or health. In intervention research, they also provide outcomes for evaluating whether a strategy changes the manner in which people eat.
Method selection should follow the behavior the study needs to quantify. Weighed records or photographs are suited to documenting consumed foods and portion sizes, whereas direct observation and video can capture meal timing, eating rate, or bite frequency. Wearable sensors are relevant when chewing is the target. Matching the recording method to the outcome improves interpretability.
A procedure may combine direct observation with weighed records, photographs, video, or wearable sensors, depending on the target outcome. Researchers can record consumed foods, portion sizes, meal timing, eating rate, bite frequency, or chewing. The resulting data provide observable or instrument-recorded measures that can be compared across participants, meals, or intervention conditions.
This approach is useful when researchers need to evaluate eating behavior beyond recalled intake. It can support studies of appetite, obesity, health, and treatment response by providing more precise information about energy intake and meal patterns. It is also valuable for testing interventions intended to change dietary choices, eating pace, or meal structure.
Objective measures can show whether an intervention changes the behavior it targets, rather than only whether participants describe a change. Depending on the intervention, outcomes may include dietary choices, consumed amounts, eating pace, meal timing, bite frequency, or chewing. Comparing these recorded features helps researchers assess treatment response and identify which aspects of meal behavior changed.