Assessment of Food Intake Using Both 3D Scanning Method and a Photographic Method

NCT07371559 | Recruiting

• 1 other identifier: SIAT-IRB-250215-H0960
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

This project aims to develop a new and more accurate method to assess energy intake in the diet by collaborating with Astravis company in Switzerland, integrating image recognition and intelligent applications, to improve the accuracy of energy assessment in the food, and to explore the application in dietary research.The researchers will recruit 200 volunteers.

Conditions

Data Collection

Keywords

food intake; food preference; food energy assessment

Outcome Measures

Primary Outcomes (4)

• BMI of the volunteers

  The volunteers' BMI is chosen between normal and underweight for easy comparison.

  This study will take about 1 year and a half to finish, starting from May 1 2025 to Dec 31 2026.

• 3D scanning of the foods chosen by volunteers using a Bodyscan3d smartphone application

  The volunteers will be asked to choose 5 out of 20 dishes in a buffet and 3D scanning of the foods chosen by volunteers will be taken using a Bodyscan3d application.

  This study will take about 1 year and a half to finish, starting from May 1 2025 to Dec 31 2026.

• Weight and name of each food

  The weight and name of the food selected by the volunteers will be systematically recorded using a digital electronic scale and food record form. This scale and food record form will be employed to ensure accurate measurements of each food item's mass that the volunteers consume throughout the study period and each food item they choose.

  This study will take about 1 year and a half to finish, starting from May 1 2025 to Dec 31 2026.

• Calories of the food chosen by the volunteers will be evaluated using the Hava smartphone application

  We use another Hava application to evaluate the calories of the food selected by the volunteers and compare with the calories we calculated, with the smaller the difference, the better the Hava assessment.

  This study will take about 1 year and a half to finish, starting from May 1 2025 to Dec 31 2026.

Study Arms (2)

Control

21.5≤BMI\<25, age between 25-40 years old, 100subjects.

Superlean

15\<BMI≤18.5, age between 25-40 years old, 100 subjects.

Eligibility Criteria

• Age: 22 Years - 40 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Participants are healthy, with no metabolic disorder, 22 - 40 years old

You may qualify if:

• Recently measured body mass index (BMI): normal control group (21.5 ≤ BMI \< 25); Recently measured body mass index (BMI): healthy underweight group (15 \< BMI ≤ 18.5); Must be able to choose the food as requested.

You may not qualify if:

• Metabolic diseases; Recent weight loss due to various disease causes; Ongoing treatment for weight loss; Eating disorders; Pregnant or lactating women; Infectious diseases such as HIV, Hepatitis; Diabetes mellitus.

Sponsors & Collaborators

• Shenzhen Institutes of Advanced Technology ,Chinese Academy of Sciences: lead

Study Sites (1)

Shenzhen Institute of Advanced Technology

Shenzhen, Guangdong, China

RECRUITING

MeSH Terms

Conditions

Food Preferences

Condition Hierarchy (Ancestors)

Feeding Behavior; Behavior

Central Study Contacts

John Roger Speakman, PhD

CONTACT

15810868669; j.speakman@abdn.ac.uk

Ying Yu, PhD

CONTACT

18513508048; y.yu@siat.ac.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: April 3, 2025
• First Posted: January 28, 2026
• Study Start: January 31, 2026
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: January 28, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)