Hip, back, waist

Ahmadi, 2020- four machine learning models to predict energy expenditure of preschoolers from raw acceleration features from hip or non-dominant wrist-worn ActiGraph accelerometers

Aittasalo, 2015- cut-points for mean amplitude deviation in adolescents wearing Hookie or ActiGraph monitors at the hip

Bai, 2016-calculates the acceleration-based metric Activity Index from a hip-worn ActiGraph accelerometer which was related to energy expenditure in adult women

Bammann, 2021- cut-points for Euclidean norm minus one for monitors worn at each hip, wrist, and ankle in older adults

Bianchim, 2022- cut-points for Euclidean norm minus one and mean amplitude deviation for monitors worn at the right hip and each wrist in children and adolescents with and without cystic fibrosis

Brage, 2003- branched and not branched models to predict energy expenditure from hip-worn CSA accelerometer counts/min and/or heart rate in adult males

Brandes, 2012- activity-specific linear regression equations for predicting energy expenditure during walking, cycling, and stair walking in children and adults using acceleration measured by a Dynaport on the lower back

Brønd, 2019- six sets of cut-points for non-proprietary counts from children wearing an ActiGraph on the right hip

Choi, 2010- five prediction models for energy expenditure in adolescents using ActiGraph counts from the hip, wrist, or ankle

Clevenger, 2022- consensus method for time spent in moderate-to-vigorous physical activity using hip-worn ActiGraph data in adults

Crotti, 2020- cut-points for Euclidean norm minus one from ActiGraph worn on right hip and each wrist in children

Crouter, 2006- a 2-regression model for hip-worn ActiGraph counts in adults

Crouter, 2007- a 2-regression model for hip-worn Actical counts in adults

Crouter, 2010- an updated 2-regression model for hip-worn ActiGraph counts in adults

Crouter, 2011- an updated 2-regression model for hip-worn Actical counts in adults

Crouter, 2012- a 2-regression model for hip-worn ActiGraph counts in children

Dibben, 2020- cut-points for two acceleration-based metrics (sum of vector magnitudes and mean amplitude deviation) for GENEActiv monitors worn at the hip and each wrist in patients with heart failure

Diniz-Sousa, 2020- regression equations and cut-points for Euclidean norm minus one, mean amplitude deviation, and vector magnitude of ActiGraph counts from ActiGraphs worn on the lower back or hip in adults with class 2 or 3 obesity

Duclos, 2015- equation to predict total energy expenditure from smartphone accelerometers in adults

Esliger, 2011- cut-points for signal magnitude vector from GENEA worn on right hip and each wrist in adults

Heil, 2006- single and 2-regression models for predicting activity energy expenditure in children and adults wearing an Actical accelerometer on the right hip or non-dominant ankle or wrist

Hibbing, 2018- four Sojourn models to predict energy expenditure of children using hip- or wrist-worn ActiGraph counts or Euclidean norm minus one

Hibbing, 2018 (2)- fifteen 2-regression models to predict energy expenditure in adults for an ActiGraph worn at the hip, each wrist and ankle using Euclidean norm minus one, gyroscope vector magnitude, and direction changes

Hikihara, 2014- a 2-regression model to predict energy expenditure in children wearing a waist-worn Omron accelerometer

Hildebrand, 2014- calculates Euclidean norm minus one from raw acceleration data of hip or non-dominant wrist-worn ActiGraph or GENEActivs with energy expenditure equations and activity intensity cut-points for children and adults

Horner, 2012- models for predicting total energy expenditure and physical activity energy expenditure for males and females during free-living using a 3dnx on the lower back

Jimmy, 2013- overall linear regression model, and a cubic 2-regression model and linear 2-regression model with separate equations for locomotor and play activities to predict energy expenditure in children wearing an ActiGraph on the hip

Johansson, 2006- branched equation model to predict energy expenditure from heart rate and counts in adults wearing a ActiGraph on the lower back

Kim, 2008- three linear regression models to predict energy expenditure in adults using waist, ankle, and wrist accelerometers

Lyden, 2014- Sojourn model to predict energy expenditure from hip-worn ActiGraph count data in adults

Mackintosh, 2016- thirteen machine learning models to predict energy expenditure in children using count data from ActiGraphs on chest, both hips, wrists, ankles, and knees

Migueles, 2021- cut-points for activity intensity using Euclidean norm minus measured at the hip or either wrist in older adults

Montoye, 2015- sixteen acceleration-based machine learning models to predict energy expenditure of adults wearing ActiGraph on thigh or hip or a GENEActiv on either wrist

Montoye, 2016 (2)- four acceleration-based machine learning models to predict energy expenditure of adults wearing ActiGraph on thigh or hip or GENEActiv on either wrist

Montoye, 2017- four acceleration-based machine learning models to predict energy expenditure of adults wearing ActiGraph on ankle, hip, or either wrist

Montoye, 2019- six machine learning models using either count or raw data from ActiGraphs on right hip or left wrist to predict energy expenditure of children

Nolan, 2014- acceleration measured by an iPod touch worn on the lower back is used to determine speed and grade of walking or running which are used to calculate energy expenditure based on pre-existing equations in adults

Ohkawara, 2011- magnitude of filtered acceleration and the ratio of unfiltered to filtered acceleration is used to determine activity type (sedentary, household, or locomotive), then activity-specific equations are used to predict energy expenditure in adults wearing a waist-worn Omron accelerometer

Phillips, 2013- cut-points for signal magnitude vector from GENEA worn on right hip and each wrist in children

Sanders, 2019- cut-points for Euclidean norm minus one from ActiGraph worn on right hip and GENEActiv worn on non-dominant wrist in older adults

Steenbock, 2019- twenty-four machine learning models to predict energy expenditure of preschoolers using acceleration metrics from an ActiGraph on either hip, GENEActiv right hip, GENEActiv on either wrist, and/or ActivPal right thigh

Tanaka, 2019- the ratio of unfiltered to filtered acceleration is used to determine non-locomotive vs. locomotive activities, then activity-specific equations are used to predict energy expenditure in young children wearing a waist-worn Omron accelerometer

Tanaka, 2007- linear and non-linear equations were developed to predict energy expenditure in young children wearing an ActivTracer on the left hip

Trost, 2016- two decision tree models for classifying activity intensity from ActiGraph counts in children with cerebral palsy wearing an ActiGraph at the hip

Vaha-Ypya, 2015- equations to predict energy expenditure and activity intensity cut-points for mean amplitude deviation were determined from adults wearing a hip-worn Hookie monitor

Vaha-Ypya, 2015 (2)- cut-points for mean amplitude deviation (MAD) that can be used for any accelerometer brand were determined from adults wearing three monitors at the hip

van Hees, 2011- prediction equations for energy expenditure for pregnant women and non-pregnant women wearing a GENEA on the wrist or non-dominant hip

Wang, 2022- linear regression and cut-points for accelerometer activity index from a hip-worn ActiGraph monitor in older women

Yamazaki, 2009- model to predict energy expenditure during walking in adults wearing a waist-worn accelerometer

Zakeri, 2012- Cross-sectional time series and multivariate adaptive regression splines for ActiHeart, ActiGraph, or ActiGraph plus heart rate inputs, resulting in six total models for predicting total energy expenditure in preschool-aged children