Validating a New Machine-Learned Accelerometer Algorithm Using Doubly Labeled Water
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity of Wisconsin, Milwaukee
About this trial
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.
Eligibility criteria
Qualifiers
must be 18+ years of age
be able to ambulate on own, unassisted, on a regular basis
speak and read English
must have access to a working smart phone and a computer with internet access
Disqualifiers
wheelchair reliant
assistive walking device reliant (cannot walk for at least 50 feet without an assistive device)
diagnosed uncontrolled hypertension (above 160/100 mgHg)
diagnosed cognitive impairment or inability to follow study procedures such as Alzheimer's disease or dementia
Trial design
Treatments tested in this trial
- Doubly-Labeled Water
Treatment groups
125 Participants
are divided into 3 treatment groupsSponsors and collaborators
University of Wisconsin, Milwaukee
Lead sponsor
University of Colorado, Denver
Collaborator
University of Massachusetts, Amherst
Collaborator
National Cancer Institute (NCI)
Collaborator
Source ClinicalTrials.gov