A smartphone-driven methodology for estimating physical activities and energy expenditure in free living conditions.
J Biomed Inform
; 52: 271-8, 2014 Dec.
Article
em En
| MEDLINE
| ID: mdl-25048352
ABSTRACT
This paper introduces a function dedicated to the estimation of total energy expenditure (TEE) of daily activities based on data from accelerometers integrated into smartphones. The use of mass-market sensors such as accelerometers offers a promising solution for the general public due to the growing smartphone market over the last decade. The TEE estimation function quality was evaluated using data from intensive numerical experiments based, first, on 12 volunteers equipped with a smartphone and two research sensors (Armband and Actiheart) in controlled conditions (CC) and, then, on 30 other volunteers in free-living conditions (FLC). The TEE given by these two sensors in both conditions and estimated from the metabolic equivalent tasks (MET) in CC served as references during the creation and evaluation of the function. The TEE mean gap in absolute value between the function and the three references was 7.0%, 16.4% and 2.7% in CC, and 17.0% and 23.7% according to Armband and Actiheart, respectively, in FLC. This is the first step in the definition of a new feedback mechanism that promotes self-management and daily-efficiency evaluation of physical activity as part of an information system dedicated to the prevention of chronic diseases.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Monitorização Ambulatorial
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Telefone Celular
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Metabolismo Energético
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Atividade Motora
Tipo de estudo:
Health_economic_evaluation
Limite:
Adolescent
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Adult
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article