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Estimation of Energy Expenditure and Physical Activity Classification With Wearables

NCT05523830 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 56

Last updated 2023-07-03

No results posted yet for this study

Summary

Regular physical activity (PA) is proven to help prevent and treat several non-communicable diseases such as heart disease, stroke, and diabetes. Intensity is a key characteristic of PA that can be assessed by estimating energy expenditure (EE). However, the accuracy of the estimation of EE based on accelerometers are lacking. It has been suggested that the addition of physiological signals can improve the estimation. How much each signal can add to the explained variation and how they can improve the estimation is still unclear.

The goal of the current study is twofold:

to explore the contribution of heart rate (HR), breathing rate (BR) and skin temperature to the estimation of EE develop and validate a statistical model to estimate EE in simulated free-living conditions based on the relevant physiological signals.

Conditions

  • Energy Metabolism
  • Algorithms

Interventions

OTHER

No Intervention

No intervention

Sponsors & Collaborators

  • Ministry of Economic Affairs

    collaborator UNKNOWN

  • Maastricht University Medical Center

    lead OTHER

Principal Investigators

  • Guy Plasqui · Maastricht University

Eligibility

Min Age
18 Years
Max Age
64 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-05-18
Primary Completion
2023-06-29
Completion
2023-06-29

Countries

  • Netherlands

Study Locations

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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 NCT05523830 on ClinicalTrials.gov