Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm
Hikihara, 2014
Last update: January 15, 2022. Updates will occur every 3 months.
Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm
Hikihara, 2014
A 2-regression model was developed in children wearing a waist-worn Omron accelerometer. The threshold of unfiltered to filtered synthetic acceleration is used to determine whether a ‘locomotive’ or ‘non-locomotive’ equation is used to predict METs. Root Mean Square Error (RMSE) was 0.508 to 0.694 METs.
Sample: 68 (42 males) healthy children, 6-12 years of age
Setting: Laboratory
Activities: Activities of daily living, video games, overground walking and running, stairs, stationary
Criterion: Douglas bag (VO2)
Accelerometer(s): Omron worn on the waist
Validation approach: Holdout of 20 participants
Synthetic acceleration was calculated (i.e., vector magnitude, square root of the sum of the squared acceleration values in each axis) before and after passing the acceleration data through a high-pass filter with a cut-off frequency of 0.7 Hz (second-order Butterworth). A threshold for the ratio of unfiltered synthetic acceleration to filtered synthetic acceleration is used to determine which regression equation to use to predict METs. If this ratio is less than 1.12, then the locomotive equation is used. Acceleration data were analyzed using a 10-s epoch. Equations are available with and without the inclusion of weight, age, and sex.
Hikihara, Y., Tanaka, C., Oshima, Y., Ohkawara, K., Ishikawa-Takata, K., & Tanaka, S. (2014). Prediction models discriminating between nonlocomotive and locomotive activities in children using a triaxial accelerometer with a gravity-removal physical activity classification algorithm. PloS One, 9(4), e94940. https://doi.org/10.1371/journal.pone.0094940 Link to Paper
Corresponding author: Yuki Hikihara, hikihara.yuki@it-chiba.ac.jp
Kimberly Clevenger at accelerometerrepository@gmail.com