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Validating a New Machine-Learned Accelerometer Algorithm Using Doubly Labeled Water

NCT05736302 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 125

Last updated 2026-05-04

No results posted yet for this study

Summary

The purpose of this study is to validate previously developed physical function-clustered specific machine-learned accelerometer algorithms to estimate total daily energy expenditure (TDEE) in individuals with general movement and functional limitations.

Conditions

Interventions

OTHER

Doubly-Labeled Water

All eligible participants will receive a dose of doubly-labeled water.

Sponsors & Collaborators

  • University of Colorado, Denver

    collaborator OTHER

  • University of Massachusetts, Amherst

    collaborator OTHER

  • National Cancer Institute (NCI)

    collaborator NIH

  • University of Wisconsin, Milwaukee

    lead OTHER

Principal Investigators

  • Scott Strath, PhD · University of Wisconsin, Milwaukee

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-03-14
Primary Completion
2026-08-28
Completion
2026-12-31

Countries

  • United States

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05736302 on ClinicalTrials.gov