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A pilot study on energy expenditure estimation through decision modelling

Title
A pilot study on energy expenditure estimation through decision modelling
Type
Chapter or Part of a Book
Year
2019
Authors
D. Bustos
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
A. P. Sposito
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
A. D. Lucena
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Book
Pages: 287-296
ISBN: 978-3-030-14729-7
Electronic ISBN: 978-3-030-14730-3
Indexing
Publicação em Scopus Scopus - 0 Citations
Other information
Authenticus ID: P-00Q-B8W
Resumo (PT):
Abstract (EN): The generation of standardized equations for predicting energy expenditure, to be applied to every healthy individual, is still subject to research. The purpose of this study was to contribute to the development of a decision algorithm to estimate energy expenditure for its application over a wide range of physical activities. Ten participants (age 31.70 ± 4.19) performed a sequence of 12 activities chosen to represent basal, light and moderate intensities. During each trial, participants wore three Actigraph accelerometers on the wrist, hip and ankle, and oxygen consumption was simultaneously measured by a portable metabolic system. From a previously developed literature research, 32 equations were selected to estimate energy requirements. Calculations and values obtained from oximetry were compared. As a result, a decision model was elaborated based on the equations which demonstrated to provide more accurate results. Future studies should be developed to validate the proposed model within bigger samples. © Springer Nature Switzerland AG 2019.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 10
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