Literature DB >> 16646354

Predicting activity energy expenditure using the Actical activity monitor.

Daniel P Heil1.   

Abstract

This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed from oxygen consumption. Regression analysis, used to create AEE prediction equations based on Actical output, varied considerably for both children (R2 = .45-.75; p < .001) and adults (R2 = .14-.85; p < .008). Most of the resulting algorithms accurately predicted accumulated AEE and time within light, moderate, and vigorous intensity categories (p > .05). The Actical monitor may be useful for predicting AEE and time variables at the ankle, hip, or wrist locations.

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Year:  2006        PMID: 16646354     DOI: 10.1080/02701367.2006.10599333

Source DB:  PubMed          Journal:  Res Q Exerc Sport        ISSN: 0270-1367            Impact factor:   2.500


  124 in total

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3.  Effect of BMI on prediction of accelerometry-based energy expenditure in youth.

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Journal:  Med Sci Sports Exerc       Date:  2012-12       Impact factor: 5.411

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Authors:  Elaine M Urbina; Thomas R Kimball; Philip R Khoury; Stephen R Daniels; Lawrence M Dolan
Journal:  J Hypertens       Date:  2010-08       Impact factor: 4.844

5.  Factors associated with objectively measured exercise participation after hospitalization for acute coronary syndrome.

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6.  Total daily activity declines more rapidly with increasing age in older adults.

Authors:  Aron S Buchman; Robert S Wilson; Lei Yu; Bryan D James; Patricia A Boyle; David A Bennett
Journal:  Arch Gerontol Geriatr       Date:  2013-08-15       Impact factor: 3.250

7.  Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

Authors:  John B Correa; John W Apolzan; Desti N Shepard; Daniel P Heil; Jennifer C Rood; Corby K Martin
Journal:  Appl Physiol Nutr Metab       Date:  2016-03-14       Impact factor: 2.665

8.  Differences in daily objective physical activity and sedentary time between women with self-reported fibromyalgia and controls: results from the Canadian health measures survey.

Authors:  Paquito Bernard; G Hains-Monfette; S Atoui; C Kingsbury
Journal:  Clin Rheumatol       Date:  2018-05-12       Impact factor: 2.980

9.  Ankle Accelerometry for Assessing Physical Activity Among Adolescent Girls: Threshold Determination, Validity, Reliability, and Feasibility.

Authors:  Erin R Hager; Margarita S Treuth; Candice Gormely; LaShawna Epps; Soren Snitker; Maureen M Black
Journal:  Res Q Exerc Sport       Date:  2015-08-19       Impact factor: 2.500

10.  Validation of the International Physical Activity Questionnaire-Short among Blacks.

Authors:  Kathleen Y Wolin; Daniel P Heil; Sandy Askew; Charles E Matthews; Gary G Bennett
Journal:  J Phys Act Health       Date:  2008-09
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