Other
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
Chuang, 2013- single regression, activity-specific regression, and a mono-exponential equation to predict energy expenditure in adults wearing accelerometers on the wrist and ankle
Curone, 2010- cut-points for signal magnitude area using ADXL330 on upper part of trunk
Duclos, 2015- equation to predict total energy expenditure from smartphone accelerometers in adults
Hiremath, 2012- a general equation and a set of four activity-specific regression equations for predicting energy expenditure of manual wheelchair users using a Sensewear armband
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
Jang, 2006- combination of 7 accelerometers (15 total axes) is used to predict energy expenditure in adults using a simple calculation converting acceleration into velocity and work
Kim, 2008- three linear regression models to predict energy expenditure in adults using waist, ankle, and wrist accelerometers
Kiuchi, 2014- twelve total models (three feature sets at four wear locations including both wrists and upper arms) were developed for predicting energy expenditure using acceleration and gyroscopic angular velocity in manual wheelchair users
Mehta- cut-points for activity intensity from raw acceleration
Nguyen, 2013- data from three monitors - a Lifecorder accelerometer at the waist, Step Watch 3 at the ankle, and a GPS unit - are combined to predict energy expenditure in adults
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
Tanaka, 2007- linear and non-linear equations were developed to predict energy expenditure in young children wearing an ActivTracer on the left 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
Weippert, 2013- four models to predict energy expenditure in adults wearing a chest-worn accelerometer
Yamazaki, 2009- model to predict energy expenditure during walking in adults wearing a waist-worn accelerometer