Nutrition AssessmentPortionSizeAINCT05343585
Validity of an AI-based Program to Identify Foods and Estimate Food Portion Size
A study testing PortionSize AI in people with Nutrition Assessment, run by Pennington Biomedical Research Center at 1 site in United States.
Trial summary
The purpose of this study is to test the accuracy of the Nutrition Artificial Intelligence in the Openfit app during meals in a controlled laboratory setting Read more about this study
- Who is it for?
- Ages 18 to 62 yearsHealthy volunteers can take part
- Conditions the study is for
- Nutrition Assessment
- What is being tested?
- PortionSize AI
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 24 participants
- Where
- 1 siteUnited States
- Study dates
- 27 Apr 2022to 3 Jun 2022
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 62 years
- All sexes
- Healthy volunteers accepted
- Adult
Who may be able to join
- Male or female
- Aged 18-62 years
- Self-reported body mass index (BMI) 18.5-50 kg/m2
Who cannot join
- Any condition or circumstance that could impede study completion
- Unfamiliar with or not able to use an iPhone
Trial locations and contacts
1 site in 1 country.
United States1 site
Pennington Biomedical Research Center
Baton Rouge, Louisiana, 70808
About this study
Official title: Testing the Validity of an Artificial Intelligence-based Program to Identify Foods and Estimate Food Portion Size Among Adults, a Pilot Study
The purpose of this study is to test the accuracy of the Nutrition Artificial Intelligence in the Openfit app during meals in a controlled laboratory setting
Read the detailed description
For this pilot study, using a convenience sample, the investigators will recruit up to 25 adults to use the Nutrition AI technology in Openfit to identify and estimate portion size of foods plated in a laboratory setting at Pennington Biomedical Research Center (PBRC) and/or Louisiana State University (LSU). Laboratory members within the Ingestive Behavioral Laboratory will also test the ability of Nutrition AI to identify foods and to quantify foods provided in the laboratory. Meals will be simulated, and participants will not consume the foods provided.
- Conditions
- Nutrition Assessment
- Being tested
- PortionSize AI
- Keywords
- Nutrition Assessment
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
PortionSize AIDevice
For this pilot study, using a convenience sample, the investigators will recruit up to 25 adults to use the Nutrition AI technology in Openfit to identify and estimate portion size of foods provided in a laboratory setting at Pennington Biomedical Research Center (PBRC) and/or Louisiana State University (LSU). Laboratory members within the Ingestive Behavioral Laboratory will also test the ability of Nutrition AI to identify foods and to quantify foods provided in the laboratory. Meals will be simulated, and participants will not consume the foods provided.
| Study group | Role | What they receive |
|---|---|---|
| Experimental | Experimental | * Training and use of Openfit
* Using the app to estimate food intake from simulated meals in a laboratory at PBRC or LSU (participants will not eat food during the meals)
* Rating the usability and satisfaction of the app Receives: Device: PortionSize AI |
What is being measured
The primary outcome is the main question the study is designed to answer.
Identification of Food Plated Using the Openfit Mobile App
Agreement surrounding identification of food and beverages provided compared with known identification, at the item level, and across all items where identification is determined by: 1) Nutrition AI without correction (automated), 2) Nutrition AI with user correction (semi-automated)
For a food identified through the Nutrition AI to be considered an exact food match, the name of the food identified must match or be a close match to the food served. For example, a fruit cocktail identified as a fruit salad is an acceptable match. Proportions will be used to assess whether the percentage of food items plated that were correctly identified by Nutrition AI is different to the percentage of foods correctly identified by a criterion method (human rater). Descriptive data will also be used to describe the frequency at which food plated was correctly identified for all food items across all participants. In total there was 255 food items tested across all participants.
Measured: One study visit of ~2 hours
Portion Size Estimation (kcal) of Food Plated Using the Openfit Mobile App
Error between mean estimates of food plated (kcal) and known food plated (kcal), determined by: 1) Nutrition AI without user correction (automated), 2) Nutrition AI with user correction (semi-automated)
Mean error and Bland-Altman analysis will be performed to determine errors in estimation of food plated from the Nutrition AI compared to estimations from the criterion measure (weighed food).
Measured: One study visit of ~2 hours
User Satisfaction of the Openfit Mobile App for Recording Food Plated
After completing assessment of food plated, participants will complete a user satisfaction survey (USS). The USS was adapted from a previous version used to assess the usability of a mobile application for dietary assessment. The USS includes five quantitative questions and three open response questions. The quantitative questions will each be scored using a 6-point Likert scale, with 1 being the lowest and worst score, and 6 being the highest and best score.
Data for each of the five quantitative responses in the USS will be averaged across participants and presented separately as mean (SD). Open responses will be evaluated using qualitative methods to identify common themes.
Measured: One study visit of ~2 hours
Usability of the Openfit Mobile App for Recording Food Plated
Participants will complete the Computer Usability Satisfaction Questionnaire (CSUQ). The CSUQ is frequently used to assess the usability of mobile applications. The CSUQ consists of 19 questions, each scored using a 7-point Likert scale (with 1 being the lowest and best score and 7 being the highest and worst score) and participants will rate satisfaction, usefulness, information quality, and interface quality of the Openfit app. The average of these 19 questions (1 being the best average score and 7 being the worst average score) provides an overall usability score.
Measured: One study visit of ~2 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Apr 2022
- Study start27 Apr 2022
- Primary completion3 Jun 2022
- Study completion3 Jun 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Nutrition AssessmentStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 24 participants (actual)
Sponsor and investigators
- Lead sponsor
- Pennington Biomedical Research Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Chloe, Pennington Biomedical Research Center
- Investigators
- Chloe P Lozano, PhD, Principal investigator, Pennington Biomedical Research Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05343585
- Sponsor's protocol ID
- PBRC 2022-011
- Other IDs
- T32DK064584
- Acronym
- PortionSizeAI
- Status last verified
- Nov 2023
- First submitted
- 12 Apr 2022
- Last updated
- 18 Nov 2023
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Any identifiers might be removed from the participants identifiable information and after such removal, the information could be used for future research studies or given to another investigator for future research without additional informed consent from the subject or legally authorized representative.
Publications
Lozano CP, Canty EN, Saha S, Broyles ST, Beyl RA, Apolzan JW, Martin CK. Validity of an Artificial Intelligence-Based Application to Identify Foods and Estimate Energy Intake Among Adults: A Pilot Study. Curr Dev Nutr. 2023 Sep 29;7(11):102009. doi: 10.1016/j.cdnut.2023.102009. eCollection 2023 Nov.
PubMed 38026571
Study at a glance
From the registry record, last updated by the sponsor on 18 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Testing the Validity of an Artificial Intelligence-based Program to Identify Foods and Estimate Food Portion Size Among Adults, a Pilot Study
- ClinicalTrials.gov ID
- NCT05343585
- Acronym / sponsor ID
- PortionSizeAI / PBRC 2022-011
- Conditions
- Nutrition Assessment
- Keywords
- Nutrition Assessment
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 24 participants (actual)
- Lead sponsor
- Pennington Biomedical Research CenterUniversity, hospital or other
- Collaborators
- National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
- Study start
- 27 Apr 2022 (actual)
- Primary completion
- 3 Jun 2022 (actual)
- Study completion
- 3 Jun 2022 (actual)
- First posted
- 25 Apr 2022 (actual)
- Results
- Posted 18 Nov 2023
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is to test the accuracy of the Nutrition Artificial Intelligence in the Openfit app during meals in a controlled laboratory setting
Detailed description
For this pilot study, using a convenience sample, the investigators will recruit up to 25 adults to use the Nutrition AI technology in Openfit to identify and estimate portion size of foods plated in a laboratory setting at Pennington Biomedical Research Center (PBRC) and/or Louisiana State University (LSU). Laboratory members within the Ingestive Behavioral Laboratory will also test the ability of Nutrition AI to identify foods and to quantify foods provided in the laboratory. Meals will be simulated, and participants will not consume the foods provided.
Study design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Experimental | Experimental | Device: PortionSize AI* Training and use of Openfit * Using the app to estimate food intake from simulated meals in a laboratory at PBRC or LSU (participants will not eat food during the meals) * Rating the usability and satisfaction of the app |
Who may qualify
- Ages
- 18 to 62 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
Key inclusion criteria (3 listed)
- Male or female
- Aged 18-62 years
- Self-reported body mass index (BMI) 18.5-50 kg/m2
Key exclusion criteria (2 listed)
- Any condition or circumstance that could impede study completion
- Unfamiliar with or not able to use an iPhone
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| PortionSize AIFor this pilot study, using a convenience sample, the investigators will recruit up to 25 adults to use the Nutrition AI technology in Openfit to identify and estimate portion size of foods provided in a laboratory setting at Pennington Biomedical Research Center (PBRC) and/or Louisiana State University (LSU). Laboratory members within the Ingestive Behavioral Laboratory will also test the ability of Nutrition AI to identify foods and to quantify foods provided in the laboratory. Meals will be simulated, and participants will not consume the foods provided. | Device | Experimental |
Primary outcome
Identification of Food Plated Using the Openfit Mobile App
Time frame: One study visit of ~2 hours
Agreement surrounding identification of food and beverages provided compared with known identification, at the item level, and across all items where identification is determined by: 1) Nutrition AI without correction (automated), 2) Nutrition AI with user correction (semi-automated) For a food identified through the Nutrition AI to be considered an exact food match, the name of the food identified must match or be a close match to the food served. For example, a fruit cocktail identified as a fruit salad is an acceptable match. Proportions will be used to assess whether the percentage of food items plated that were correctly identified by Nutrition AI is different to the percentage of foods correctly identified by a criterion method (human rater). Descriptive data will also be used to describe the frequency at which food plated was correctly identified for all food items across all participants. In total there was 255 food items tested across all participants.
Portion Size Estimation (kcal) of Food Plated Using the Openfit Mobile App
Time frame: One study visit of ~2 hours
Error between mean estimates of food plated (kcal) and known food plated (kcal), determined by: 1) Nutrition AI without user correction (automated), 2) Nutrition AI with user correction (semi-automated) Mean error and Bland-Altman analysis will be performed to determine errors in estimation of food plated from the Nutrition AI compared to estimations from the criterion measure (weighed food).
User Satisfaction of the Openfit Mobile App for Recording Food Plated
Time frame: One study visit of ~2 hours
After completing assessment of food plated, participants will complete a user satisfaction survey (USS). The USS was adapted from a previous version used to assess the usability of a mobile application for dietary assessment. The USS includes five quantitative questions and three open response questions. The quantitative questions will each be scored using a 6-point Likert scale, with 1 being the lowest and worst score, and 6 being the highest and best score. Data for each of the five quantitative responses in the USS will be averaged across participants and presented separately as mean (SD). Open responses will be evaluated using qualitative methods to identify common themes.
Usability of the Openfit Mobile App for Recording Food Plated
Time frame: One study visit of ~2 hours
Participants will complete the Computer Usability Satisfaction Questionnaire (CSUQ). The CSUQ is frequently used to assess the usability of mobile applications. The CSUQ consists of 19 questions, each scored using a 7-point Likert scale (with 1 being the lowest and best score and 7 being the highest and worst score) and participants will rate satisfaction, usefulness, information quality, and interface quality of the Openfit app. The average of these 19 questions (1 being the best average score and 7 being the worst average score) provides an overall usability score.
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 Nov 2023.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Derived from this study: PubMed 38026571Lozano CP, Canty EN, Saha S, Broyles ST, Beyl RA, Apolzan JW, Martin CK. Validity of an Artificial Intelligence-Based Application to Identify Foods and Estimate Energy Intake Among Adults: A Pilot Study. Curr Dev Nutr. 2023 Sep 29;7(11):102009. doi: 10.1016/j.cdnut.2023.102009. eCollection 2023 Nov.
- Individual participant dataSharing planned: No. Any identifiers might be removed from the participants identifiable information and after such removal, the information could be used for future research studies or given to another investigator for future research without additional informed consent from the subject or legally authorized representative.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Chloe P Lozano, PhD principal investigator
Pennington Biomedical Research Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing PortionSize AI in people with Nutrition Assessment, run by Pennington Biomedical Research Center at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 18 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 18 Nov 2023). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Identification of Food Plated Using the Openfit Mobile App (time frame: One study visit of ~2 hours). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05343585, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 18 Nov 2023.