Lab-based validation of different data processing methods for wrist-worn ActiGraph accelerometers in young adults.

Identifying bedrest using 24-h waist or wrist accelerometry in adults

OBJECTIVES To adapt and refine a previously-developed youth-specific algorithm to identify bedrest for use in adults. The algorithm is based on using an automated decision tree (DT) analysis of accelerometry data. DESIGN Healthy adults (n = 141, 85 females, 19-69 years-old) wore accelerometers on the waist, with a subset also wearing accelerometers on the dominant wrist (n = 45). Participants...

Calibration and Validation of a Wrist- and Hip-Worn Actigraph Accelerometer in 4-Year-Old Children

INTRODUCTION To determine time spent at different physical activity intensities, accelerometers need calibration. The aim of this study was to develop and cross-validate intensity thresholds for the Actigraph GT3X+ accelerometer for wrist and hip placement in four-year-old children. METHODS In total 30 children (49 months, SD 3.7) were recruited from five preschools in Stockholm. Equipped wit...

Intensity Thresholds on Raw Acceleration Data: Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) Approaches

OBJECTIVES (1) To develop and internally-validate Euclidean Norm Minus One (ENMO) and Mean Amplitude Deviation (MAD) thresholds for separating sedentary behaviours from common light-intensity physical activities using raw acceleration data collected from both hip- and wrist-worn tri-axial accelerometers; and (2) to compare and evaluate the performances between the ENMO and MAD metrics. METHOD...

Calibration And Cross-validation Of Wrist Worn Actigraph Gt3x+ In Young Preschoolers

A random forest classifier for the prediction of energy expenditure and type of physical activity from wrist and hip accelerometers.

Wrist accelerometers are being used in population level surveillance of physical activity (PA) but more research is needed to evaluate their validity for correctly classifying types of PA behavior and predicting energy expenditure (EE). In this study we compare accelerometers worn on the wrist and hip, and the added value of heart rate (HR) data, for predicting PA type and EE using machine lear...