Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables

Masse, Louise, Fuemmeler, Bernard F., Anderson, Cheryl, Matthews, Charles E., Trost, Stewart G., Catellier, Diane, & Triuth, Margarita (2005) Accelerometer data reduction : a comparison of four reduction algorithms on select outcome variables. Medicine and Science in Sports and Exercise, 37(11), S544-S554.

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Abstract

Purpose

Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction.

Methods

The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set.

Results

The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables.

Conclusions

These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

Impact and interest:

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304 citations in Web of Science®

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ID Code: 71492
Item Type: Journal Article
Refereed: Yes
DOI: 10.1249/01.mss.0000185674.09066.8a
ISSN: 1530-0315
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Deposited On: 13 May 2014 03:54
Last Modified: 13 May 2014 03:54

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