Reduction of Energy Intake Using Just-in-time Feedback from a Wearable Sensor System

Overview

Journal Obesity (Silver Spring)

Specialties Endocrinology
Nutritional Sciences
Physiology

Date 2017 Feb 25

PMID 28233942

Citations 10

Authors

Muhammad Farooq

Megan A McCrory

Edward Sazonov

Affiliations

Soon will be listed here.

Abstract

Objective: This work explored the potential use of a wearable sensor system for providing just-in-time (JIT) feedback on the progression of a meal and tested its ability to reduce the total food mass intake.

Methods: Eighteen participants consumed three meals each in a lab while monitored by a wearable sensor system capable of accurately tracking chew counts. The baseline visit was used to establish the self-determined ingested mass and the associated chew counts. Real-time feedback on chew counts was provided in the next two visits, during which the target chew count was either the same as that at baseline or the baseline chew count reduced by 25% (in randomized order). The target was concealed from the participant and from the experimenter. Nonparametric repeated-measures ANOVAs were performed to compare mass of intake, meal duration, and ratings of hunger, appetite, and thirst across three meals.

Results: JIT feedback targeting a 25% reduction in chew counts resulted in a reduction in mass and energy intake without affecting perceived hunger or fullness.

Conclusions: JIT feedback on chewing behavior may reduce intake within a meal. This system can be further used to help develop individualized strategies to provide JIT adaptive interventions for reducing energy intake.

Citing Articles

Detection of Food Intake Sensor's Wear Compliance in Free-Living.

Ghosh T, Hossain D, Sazonov E IEEE Sens J. 2022; 21(24):27728-27735.

PMID: 35813985 PMC: 9268495. DOI: 10.1109/jsen.2021.3124203.

NeckSense: A Multi-Sensor Necklace for Detecting Eating Activities in Free-Living Conditions.

Zhang S, Zhao Y, Nguyen D, Xu R, Sen S, Hester J Proc ACM Interact Mob Wearable Ubiquitous Technol. 2021; 4(2).

PMID: 34222759 PMC: 8248934. DOI: 10.1145/3397313.

A Systematic Review of Technology-Driven Methodologies for Estimation of Energy Intake.

Doulah A, McCrory M, Higgins J, Sazonov E IEEE Access. 2020; 7:49653-49668.

PMID: 32489752 PMC: 7266287. DOI: 10.1109/access.2019.2910308.

Noninvasive Continuous Monitoring of Vital Signs With Wearables: Fit for Medical Use?.

Jacobsen M, Dembek T, Kobbe G, Gaidzik P, Heinemann L J Diabetes Sci Technol. 2020; 15(1):34-43.

PMID: 32063034 PMC: 7783016. DOI: 10.1177/1932296820904947.

Validation of Sensor-Based Food Intake Detection by Multicamera Video Observation in an Unconstrained Environment.

Farooq M, Doulah A, Parton J, McCrory M, Higgins J, Sazonov E Nutrients. 2019; 11(3).

PMID: 30871173 PMC: 6472006. DOI: 10.3390/nu11030609.

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