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Digital Food Sensing and Ingredient Analysis Techniques to Facilitate Human-Food Interface Designs

Published: 07 October 2024 Publication History

Abstract

Interactive technologies that shape the traditional human-food experiences are being explored under the emerging field of Human-Food Interaction (HFI). A key challenge in developing HFI technologies is the digital sensing of food, beverages, and their ingredients, commonly known as digital food sensing. Digital food sensing involves recognizing different food and beverages and their internal attributes, such as volume and ingredients (e.g., salt and sugar content). Contemporary research on interactive food applications, such as dietary assessment, primarily employs Computer Vision (CV) techniques to identify food; however, they are ineffective when (1) identifying food’s internal attributes, (2) discriminating visually similar food and beverages, and (3) seamlessly integrating with people’s natural interactions while consuming food. Thus, this article reviews potential food and beverage sensing technologies that can facilitate novel Human-Food Interfaces, primarily focusing on non-disruptive sensing techniques to analyze food and beverages during consumption. First, we review ten different digital food sensing techniques and their applications in four categories. Then, we discuss three main aspects to consider when adopting these food-sensing techniques for human-food interface designs. Finally, we suggest the future research requirements in digital food sensing methodologies, followed by potential applications of digital food sensing in future developments of Human-Food Interfaces.

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cover image ACM Computing Surveys
ACM Computing Surveys  Volume 57, Issue 1
January 2025
984 pages
EISSN:1557-7341
DOI:10.1145/3696794
  • Editors:
  • David Atienza,
  • Michela Milano
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2024
Online AM: 30 July 2024
Accepted: 15 July 2024
Revised: 01 June 2024
Received: 08 May 2023
Published in CSUR Volume 57, Issue 1

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  1. Human-food interaction
  2. food recognition
  3. food sensing
  4. ingredient sensing

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