A Smartphone Application to Evaluate Energy Expenditure and Duration of Moderate-intensity Activities
NCT ID: NCT01995253
Last Updated: 2024-04-03
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
16 participants
INTERVENTIONAL
2012-09-30
2013-10-31
Brief Summary
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Detailed Description
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Thus, the proposed EE estimation function has been created using accelerometry data collected from 10 volunteers equipped with a smartphone and two research sensors (Armband and Actiheart) used to estimate EE during several controlled activities. The research sensors' data serves as reference during the creation and evaluation of the proposed function.
It has been evaluated with data of 6 other volunteers in free-living conditions. This new EE function using the smartphone technology is dedicated to light- and moderate-intensity activities, and we believe it can be a new way to help people controlling their daily physical activity level.
Conditions
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Study Design
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RANDOMIZED
PARALLEL
PREVENTION
NONE
Study Groups
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Controlled conditions
Energy expenditure estimation in controlled conditions
Volunteers were asked to perform several activities such as walking at different paces, running, sitting, standing still or taking public transportation for about 3h30 They wore 2 research sensors that estimate energy expenditure: Armband and Actiheart. They also wore a smartphone (in a front pant pocket) that collected accelerometry data.
Free-living conditions
Energy expenditure estimation in free-living conditions
Volunteers were asked to wear sensors during about 12 hours, one day. They wore 2 research sensors that estimate energy expenditure: Armband and Actiheart. They also wore a smartphone (in a front pant pocket) that collected accelerometry data.
Interventions
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Energy expenditure estimation in controlled conditions
Volunteers were asked to perform several activities such as walking at different paces, running, sitting, standing still or taking public transportation for about 3h30 They wore 2 research sensors that estimate energy expenditure: Armband and Actiheart. They also wore a smartphone (in a front pant pocket) that collected accelerometry data.
Energy expenditure estimation in free-living conditions
Volunteers were asked to wear sensors during about 12 hours, one day. They wore 2 research sensors that estimate energy expenditure: Armband and Actiheart. They also wore a smartphone (in a front pant pocket) that collected accelerometry data.
Eligibility Criteria
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Inclusion Criteria
* age: 18-60 years
* BMI between 18.5 and 25 kg/m²
* subject considered as healthy after clinical examination and medical questionnaire
* women of childbearing age: negative beta-HCG
* subject with normal rest electrocardiogram (validated by a cardiologist)
* subject with normal blood pressure (\<140/90 mm Hg) with or without medical treatment
* subject with no foot pad problem
* subject giving his/her written informed consent
* subject willing to comply with study procedures
* affiliated to National Health Insurance
Exclusion Criteria
* known cardiac decompensation or myocardial infarction
* surgery made less than 6 months before the study beginning
* pregnant women and nursing mother
* current infectious pathology
* abnormal electrocardiogram
* not affiliated to national health insurance people
* under legal guardianship
* refusal to sign informed consent
* refusal to be registered on the national volunteers data file
* currently participating or who having got 4500€ in this year before to have participated in another clinical trial
18 Years
60 Years
ALL
Yes
Sponsors
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Almerys
OTHER
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
OTHER
Responsible Party
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Martine DUCLOS
PUPH
Locations
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Centre de Recherche en Nutrition Humaine Auvergne
Clermont-Ferrand, , France
Countries
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Other Identifiers
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2012-A00809-34
Identifier Type: OTHER
Identifier Source: secondary_id
AU979
Identifier Type: -
Identifier Source: org_study_id
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