Clinical Trials Directory

Trials / Completed

CompletedNCT05335889

Wearable Sensors and Artificial Intelligence for Carbohydrate Counting

Feasibility of Using Wearable Sensors and Artificial Intelligence for Carbohydrate Counting in Chinese Americans With Type 2 Diabetes

Status
Completed
Phase
Study type
Observational
Enrollment
12 (actual)
Sponsor
NYU Langone Health · Academic / Other
Sex
All
Age
18 Years – 99 Years
Healthy volunteers
Not accepted

Summary

This is a one-group pilot study where Chinese immigrants who are English speaking with T2D from NYU Langone Health and NYU Brooklyn Family Health Center (Sunset Park) will be recruited.

Detailed description

To evaluate the estimation accuracy using eButton, researchers will collect carbohydrate data via weighing food by registered dietitian nutritionist (RDN) ("gold standard") (2 days/week at research labs) and food diaries by participants (2 days/week at research labs and 3 days/ week at participant home). Then, the estimated carb grams will be compared head to head among each other. Assessment will be at 0 and 2 weeks, including surveys and qualitative audio interview.

Conditions

Interventions

TypeNameDescription
DEVICEeButtonThe eButton is a wearable camera that takes pictures every 6 seconds of whatever is in front of participants. The recorded data are processed by algorithms to determine food names, volumes, and nutrient value of the consumed food (e.g., grams of carbohydrates). The eButton is a wearable device containing a multicore microprocessor, a rechargeable battery capable of 10-15 hours of continuous operation (upon a flexible choice of battery capacity), a miniSD card for data storage.
DEVICEContinuous Glucose Monitoring (CGM)The use of this device provides ambulatory glucose profiles, giving graphic and quantitative information on 24-hour glucose patterns. It does not require finger-prick testing for calibration. The system consists of a reader and a sensor (35 mm x 5 mm). The sensor is applied to the back of a person's arm. The sensor automatically measures interstitial glucose at 15-minute intervals during daily activities like work, sleep, eating, and exercise. It is able to store blocks of glucose data for 14 days.

Timeline

Start date
2022-07-18
Primary completion
2023-09-22
Completion
2023-09-22
First posted
2022-04-20
Last updated
2024-04-12

Locations

1 site across 1 country: United States

Source: ClinicalTrials.gov record NCT05335889. Inclusion in this directory is not an endorsement.