Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
This study will provide food for the participants, and they will independently choose their preferred food for consumption according to their usual dietary habits. This study will take 3D scanning and photography of the food plates before and after eating to analyze the energy intake by each participant.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control | 21.5≤BMI<25, age between 25-40 years old, 100subjects. | ||
| Superlean | 15\ |
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| 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. |
Not provided
Not provided
Inclusion Criteria:
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.
Exclusion Criteria:
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.
Not provided
Not provided
Participants are healthy, with no metabolic disorder, 22 - 40 years old
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| John Roger Speakman, PhD | Contact | 15810868669 | j.speakman@abdn.ac.uk | |
| Ying Yu, PhD | Contact | 18513508048 | y.yu@siat.ac.cn |
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Shenzhen Institute of Advanced Technology | Recruiting | Shenzhen | Guangdong | China |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D005518 | Food Preferences |
| ID | Term |
|---|---|
| D005247 | Feeding Behavior |
| D001519 | Behavior |
Not provided
Not provided
Not provided
Not provided
Not provided