Reliable recognition of lying, sitting, and standing with a hip-worn accelerometer.

Hip-worn accelerometers are widely used to estimate physical activity (PA), but the accuracy of acceleration threshold-based analysis is compromised when it comes to identifying stationary and sedentary behaviors, let alone classifying body postures into lying, sitting, or standing. The purpose of this study was to devise a novel method for accurate classification of body posture using triaxial data from hip-worn accelerometer and to evaluate its performance in free-living conditions against a thigh-worn accelerometer. The posture classification rested on 2 facts: constant Earth's gravity vector and upright walking posture. Thirty healthy adults wore a hip-mounted accelerometer and underwent an array of lying, sitting, standing, and walking tasks. Task type, their order, and length were randomly assigned to each participant. During walking, the accelerometer orientation in terms of gravity vector was taken as reference, and the angle for posture estimation (APE) was determined from the incident accelerometer orientation in relation to the reference vector. Receiver operating characteristic (ROC) curve yielded an optimal cut-point APE of 64.9° (sensitivity 100% and specificity 100%) for lying and sitting and 11.6° (94.2%; 94.5%) for sitting and standing. In free-living conditions, high agreement (89.2% for original results and 90.4% for median-filtered results) in identifying sedentary periods (sitting and lying) was observed between the results from hip- and thigh-worn accelerometers. Walking provides a valid reference activity to determine the body posture. The proposed APE analysis of the raw data from hip-worn triaxial accelerometer gives accurate and specific information about daily times spent lying, sitting, and standing.