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Updated: May 3, 2026
A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers
Published on: April 21, 2017
Recovering physical activity missing data measured by accelerometers: a comparison of individual and group-centered
Jie Zhuang1, Peijie Chen1, Chao Wang1
1Shanghai University of Sport, 399 Chang Hai Road, Shanghai 200438, PR China.
Purpose:
The purpose of this study was to determine which method, individual information-centered (IIC) or group information-centered (GIC), is more efficient in recovering missing physical activity (PA) data.
Method:
A total of 2,758 Chinese children and youth aged 9 to 17 years old (1,438 boys and 1,320 girls) wore ActiGraph GT3X/GT3X+ accelerometers for 7 consecutive days. Those with no missing data (n = 900) were used to form a nonmissing sample, which, based on a semisimulation approach, was used to create a missing data set to evaluate a set of recovery methods, including 2 IIC and 22 GIC methods. Root mean square difference (RMSD), mean signed difference, and paired t test were used to determine the effectiveness of the recovery methods.
Results:
The smallest RMSD values, which represent the most accurate recovery, were found with: (a) GIC-Expectation-maximization (GIC-EM) regardless of gender and by age (113,957.64); (b) GIC-EM regardless of gender and age (114,367.88); (c) GIC-EM regardless of age and by gender (114,697.06); (d) GIC-EM by gender and age (116,178.34); and (e) IIC averaging of remaining days (125,851.23).
Conclusion:
To recover 7-day PA accelerometer-determined activity missing data, we recommend using the GIC-EM and IIC approaches.
