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

Recruiting now

Conditions studied: Movement Disorders, Energy Metabolism

In brief

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.

Key facts

Study ID

NCT05736302

Run by

University of Wisconsin, Milwaukee

People needed

125

Starts

2023-03-14

Expected to finish

2026-12-31

Last updated by the study team

2026-05-04

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: accepted.

You may qualify if…

• 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

You may not qualify if…

• 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
• cannot take metabolic altering medications
• cannot be pregnant
• cannot be breastfeeding
• cannot use supplemental oxygen
• cannot completed required study activities for any reason
• cannot have a resting heart rate > 100 bpm or a resting blood pressure > 160 mgHg during Visit 1
• cannot weigh more than 450 lbs

Where it is running

• University of Wisconsin-Milwaukee — Milwaukee, Wisconsin, United States (enrolling)

Full record on ClinicalTrials.gov

Trial information comes from ClinicalTrials.gov and is refreshed daily. TrialsForMe does not provide medical care and does not run the studies it lists.