Validating Machine -Learned Classifiers of Sedentary Behavior and Physical Activity

Completed · Not applicable

Conditions studied: Physical Activity, Sedentary Lifestyle

In brief

The majority of the US population spends most of the day sitting and the we have new scientific evidence that this can contribute to poor health regardless of how much physical activity a person does. However, we do not measure sitting time very accurately and when we ask people to tell us how much they do, their answers are unreliable. Our study will use small sensors to objectively measure when people sit or do physical activity, and we will use sophisticated computational techniques to summarize these movement patterns.

Key facts

Study ID
NCT01775826
Run by
University of California, San Diego
People needed
225
Starts
2013-03-01
Expected to finish
2016-04-01
Last updated by the study team
2019-08-20

Who can join

Age: 6 and older, up to 85. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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