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Full-Text Articles in Medicine and Health Sciences
A Consensus Method For Estimating Physical Activity Levels In Adults Using Accelerometry, Kimberly A. Clevenge, Kelly A. Mackintosh, Melitta A. Mcnarry, Karin A. Pfeiffer, M Benjamin Nelson, Joshua M. Bock, Mary T. Imboden, Leonard A. Kaminsky, Alexander H.K. Montoye
A Consensus Method For Estimating Physical Activity Levels In Adults Using Accelerometry, Kimberly A. Clevenge, Kelly A. Mackintosh, Melitta A. Mcnarry, Karin A. Pfeiffer, M Benjamin Nelson, Joshua M. Bock, Mary T. Imboden, Leonard A. Kaminsky, Alexander H.K. Montoye
Faculty Publications - Department of Kinesiology
Identifying the best analytical approach for capturing moderate-to-vigorous physical activity (MVPA) using accelerometry is complex but inconsistent approaches employed in research and surveillance limits comparability. We illustrate the use of a consensus method that pools estimates from multiple approaches for characterising MVPA using accelerometry. Participants (n = 30) wore an accelerometer on their right hip during two laboratory visits. Ten individual classification methods estimated minutes of MVPA, including cut-point, two-regression, and machine learning approaches, using open-source count and raw inputs and several epoch lengths. Results were averaged to derive the consensus estimate. Mean MVPA ranged from 33.9–50.4 min across individual …
Statistical Learning Methods To Predict Activity Intensity From Body-Worn Accelerometers, Drew M. Lazar, Munni Begum, Monzur Murshed, Benjamin Nelson, Joshua M. Bock, Mary T. Imboden, Leonard Kaminsky, Alex Hk Montoye
Statistical Learning Methods To Predict Activity Intensity From Body-Worn Accelerometers, Drew M. Lazar, Munni Begum, Monzur Murshed, Benjamin Nelson, Joshua M. Bock, Mary T. Imboden, Leonard Kaminsky, Alex Hk Montoye
Faculty Publications - Department of Kinesiology
 Physical activity, especially when performed at moderate or vigorous intensity, has short- and long-term health benefits, but measurement of free-living physical activity is challenging. Accelerometers are popular tools to assess physical activity, although accuracy of conventional accelerometer analysis methods is suboptimal. This study developed and tested statistical learning models for assessing activity intensity from body-worn accelerometers. Twenty-eight adults performed 10-21 activities of daily living in two visits while wearing four accelerometers (right hip, right ankle, both wrists). Accelerometer placement is of crucial practical concern and this paper addresses this issue. Boosting, bagging, random forest and decision tree models were …
Validation Of Accelerometer-Based Energy Expenditure Prediction Models In Structured And Simulated Free-Living Settings, Alexander H. K. Montoye, Scott A. Conger, Christopher P. Connolly, Mary T. Imboden, M. Benjamin Nelson, Josh M. Bock, Leonard A. Kaminsky
Validation Of Accelerometer-Based Energy Expenditure Prediction Models In Structured And Simulated Free-Living Settings, Alexander H. K. Montoye, Scott A. Conger, Christopher P. Connolly, Mary T. Imboden, M. Benjamin Nelson, Josh M. Bock, Leonard A. Kaminsky
Faculty Publications - Department of Kinesiology
This study compared accuracy of energy expenditure (EE) prediction models from accelerometer data collected in structured and simulated free-living settings. Twenty-four adults (mean age 45.8 years, 50% female) performed two sessions of 11 to 21 activities, wearing four ActiGraph GT9X Link activity monitors (right hip, ankle, both wrists) and a metabolic analyzer (EE criterion). Visit 1 (V1) involved structured, 5-min activities dictated by researchers; Visit 2 (V2) allowed participants activity choice and duration (simulated free-living). EE prediction models were developed incorporating data from one setting (V1/V2; V2/V2) or both settings (V1V2/V2). The V1V2/V2 method had the lowest root mean square …