RecruitingNCT05736302

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

Sponsor

University of Wisconsin, Milwaukee

Enrollment

125 participants

Start Date

Mar 14, 2023

Study Type

OBSERVATIONAL

Conditions

Movement Disorders Energy Metabolism

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.

Eligibility

Min Age: 18 Years

Inclusion Criteria4

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

Exclusion Criteria11

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