Diet Habit Clinical Trial
Official title:
Validation Study of a Passive Image-Assisted Dietary Assessment With Automated Image Analysis Process
Verified date | November 2020 |
Source | The University of Tennessee, Knoxville |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
The purpose of this investigation is to validate a passive image-assisted dietary assessment method using images taken by Sony Smarteyeglass and an automatic image analysis software, DietCam, to identify food items and estimate portion sizes. Participants will be randomized into one of the two orders of meals (Order 1 and 2). In each meal, participants will be given a meal that includes a regular-shaped single food (i.e., cookie), an irregular-shape single food (i.e., ice cream), a regular-shaped mixed food (i.e., sandwich), and irregular-shaped mixed food (i.e., pasta dish).
Status | Completed |
Enrollment | 30 |
Est. completion date | June 3, 2020 |
Est. primary completion date | August 3, 2018 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 65 Years |
Eligibility | Inclusion Criteria: - between the ages of 18 and 65 years; - body mass index (BMI) 18.5 to 24.9 kg/m2; - no food allergies/intolerance to foods used in the investigation; - report not having a dietary plan or dietary restrictions that prevents consumption of the foods used in the investigation; - report a favorable preference for the foods served in the meal, with participants rate each food item 3 on a Likert scale during the phone screen; - able to complete all two meal sessions within four weeks of the screening session; - are not legally blind without corrected lenses; and - are able to eat a meal while wearing the Sony Smarteyeglass. Exclusion Criteria: - wear electronic medical devices such as pacemakers and implantable defibrillators |
Country | Name | City | State |
---|---|---|---|
United States | Healthy Eating and Activity Laboratory, University of Tennessee | Knoxville | Tennessee |
Lead Sponsor | Collaborator |
---|---|
The University of Tennessee, Knoxville |
United States,
He H, Kong F, Tan J. DietCam: Multiview Food Recognition Using a Multikernel SVM. IEEE J Biomed Health Inform. 2016 May;20(3):848-855. doi: 10.1109/JBHI.2015.2419251. Epub 2015 Apr 2. — View Citation
Lohman TR, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign,Illinois: Human Kinetics Books; 1988.
Sony Coporation. Smarteyeglass: API Overview. 2017; https://developer.sony.com/develop/wearables/smarteyeglass-sdk/api-overview/. Accessed Feb, 2017.
U.S. Department of Health and Human Services; U.S. Department of Agriculture. 2015-2020 Dietary guidelines for Americans. Appendix 2. Estimated Calorie Needs per Day, by Age, Sex, and Physical Activity Level 2015; 8th Edition:http://health.gov.dietaryguidelines/2015/guidelines/. Accessed April 18, 2017.
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Weighed Food Intake | Before and after each meal session, each food items will be weighed to the nearest tenth of a gram using an electronic food scale. Assessing the weight change of food intake. | Meal session 1 and 2 within 4 weeks of initial screening session | |
Primary | DietCam | DietCam is developed by Dr. JinDong Tan and colleagues and is an application designed to automatically recognize foods and estimate volumes of a meal from images or videos without any reference objects. In this investigation, DietCam will be used to identify food items with different shapes (Regular vs Irregular) and complexities (Single food vs Mixed food). DietCam will also be used to estimate volume of foods in the unit of cubic meters (m3). Results of volume estimation of foods from DietCam will be entered to NDS-R to convert to commonly used measurements. Assessing weight change of food intake. | Meal session 1 and 2 within 4 weeks of initial screening session | |
Primary | 24-hour Dietary Recall | On the following day of each meal session, the investigator will ask the participant to recall their dietary intake by having the participant reporting all foods and beverages consumed and the time in which they consumed these items within the past 24 hours. Participants will be asked what time of day the foods and beverages were consumed and will be shown two-dimensional food shapes to help with estimating portion sizes. Only dietary intake for the meal session will be entered into NDS-R to convert to commonly used measurements. | The following day of meal session 1 and 2 within 4 weeks of initial screening session | |
Secondary | Sony Smarteyeglass | Digital images will be recorded during each meal session using Sony Smarteyeglass. Number of blurred images and times that Sony Smarteyeglass fail to capturing images will be documented. | During Meal session 1 and 2 within 4 weeks of initial screening session | |
Secondary | Participants' Feedback | At the end of last meal session, participants will be asked to complete a questionnaire regarding their experience on using Sony Smarteyeglass. A total of six structured questions will be included in the questionnaire and each question will be associated with an open-ended question. Structured questions will consist of a five-scale rating regarding ease of use, clearness of instructions, satisfaction, likelihood, and comfortableness. Percentages of participants answering in responses to each structured question will be tabulated and open-ended questions will be summarized. | Meal session 2 within 4 weeks of initial screening session |
Status | Clinical Trial | Phase | |
---|---|---|---|
Active, not recruiting |
NCT04420936 -
Pragmatic Research in Healthcare Settings to Improve Diabetes and Obesity Prevention and Care for Our Program
|
N/A | |
Completed |
NCT04025099 -
Internal Cues Versus External Cues for Eating and Activity
|
N/A | |
Completed |
NCT04766528 -
Effect of Diet on the Microbiota / Endoccanabinoidome Axis in Response to Physical Activity
|
N/A | |
Completed |
NCT03277040 -
Diet, Eating, and Lifestyle Improvement for Valued Employees and Their Relatives
|
N/A | |
Active, not recruiting |
NCT05544461 -
Piloting a Web-based Personalised Nutrition App (eNutri) With UK University Students
|
N/A | |
Active, not recruiting |
NCT04748835 -
The SEEA (SCI Energy Expenditure and Activity) Study
|
||
Active, not recruiting |
NCT04991142 -
Models of Nutrition From Continuous Glucose Monitors
|
||
Recruiting |
NCT04487015 -
A Digital Approach to Improving Carbohydrate Periodisation Behaviours in Athlete: SMART+ Study
|
N/A | |
Completed |
NCT03748056 -
Targeted Food Incentives to Improve Diet Quality and Health Among Adults
|
N/A | |
Not yet recruiting |
NCT05960396 -
Exploring the Mechanism of Dietary Pattern Improving MAFLD
|
N/A | |
Enrolling by invitation |
NCT04314882 -
The Danish National Survey of Diet and Physical Activity 2021-2023
|
||
Terminated |
NCT04677322 -
TO ASSESS THE EFFECTIVENESS OF THE INTERVENTION OF THE LOW-SODIUM DIET IN PATIENTS WITH HTA
|
||
Completed |
NCT03855098 -
Biomarkers of Food Intake Using a Cross-over Feeding Study
|
N/A | |
Completed |
NCT03124446 -
Mindfulness-Based College: Stage 1
|
N/A | |
Completed |
NCT03993652 -
Kids FIRST: Family-based Intervention to Reduce Snacking and Screen Time in Children
|
N/A | |
Completed |
NCT04766034 -
Impact of Behavioral Economic Strategies on Low-Income Older Adults' Food Choices in Online Retail Settings
|
N/A | |
Completed |
NCT03913871 -
Text Message Program to Improve Eating Behaviors Among African Americans in New Orleans
|
N/A | |
Completed |
NCT03698123 -
Performance Nutrition for Residents and Fellows
|
N/A | |
Completed |
NCT03941392 -
Nutritional Study in Spanish Pediatric Population
|
||
Completed |
NCT03400566 -
Effects of Experiential Learning on Vegetable Intake in Preschool Children
|
N/A |