Evidence map›Paper›PMID 42197096›Full record

ArticleNutrients2026

Enhancing Nutritional Ingestive Behavior Microstructure Detection: Video Annotation and Passive Sensing Approaches.

Kathleen J Melanson, Edison Thomaz, Nathan DeSalvo, Cody J Arvonen, Adeleke J Akinkurolere, Theodore A Walls

Abstract read
In one paragraph

Article in Nutrients, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Kathleen J MelansonDepartment of Nutrition, University of Rhode Island, Kingston, RI 02881, USA.ORCID 0000-0002-4114-7266
Edison ThomazDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0001-8188-0457
Nathan DeSalvoDepartment of Psychology, University of Rhode Island, Kingston, RI 02881, USA.
Cody J ArvonenDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA.ORCID 0009-0009-1950-3963
Adeleke J AkinkurolereDepartment of Nutrition, University of Rhode Island, Kingston, RI 02881, USA.
Theodore A WallsDepartment of Psychology, University of Rhode Island, Kingston, RI 02881, USA.

Funding

NIDDK NIH HHS 5R01DK134546‑02NIH HHS 5R01DK134546‑02
6 · The paper itself

Abstract

BACKGROUND/

objectivesUnderstanding the microstructure of ingestive behavior (IB) is critically important to the development and success of interventions to change eating rates and produce more optimal food energy intake outcomes. Detailed measurement of IB microstructure is needed to guide development of real-time sensing approaches that can support such interventions. This article summarizes novel measurement and inference strategies around both digital video and inertial motion sensors in a structured laboratory protocol.

methodsDigital video footage was annotated for chews and bites and analyzed with generalized additive models to assess differences in IB for each of four meal courses varying by food texture.

resultsSignificant differences were revealed in IB microstructure in the form of nonlinear patterns of annotated video footage and initial sensing tests, indicating an optimal sensor location over the jaw's condyle bone.

conclusionsFindings of an intensive longitudinal multicourse full meal protocol reflect important differences in nonlinear trends of eating behavior for diverse texture foods. These differences inform further development of technology-aided measurement strategies, provide an experimental protocol for fieldwide IB inquiry, and reveal expected fundamental differences in ingestion rates. Further inquiry into the underlying causes of nonlinearities for high UPF foods, along with sensor measurements, is warranted.

Indexed as

EatingFeeding BehaviorVideo RecordingEnergy IntakeHumansMasticationMotion Capturebehavioral sensorseating detectioningestive behavior microstructurewearable technology

Identifiers

PMID42197096
PMCPMC13209229

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.