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Modeling physical activity outcomes from wearable monitors.

Daniel P Heil¹, Soren Brage, Megan P Rothney

¹Department of Health and Human Development, Movement Science/Human Performance Lab, Montana State University, Bozeman, MT 59717-3360, USA. dheil@montana.edu

Medicine and Science in Sports and Exercise

|December 14, 2011

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This study introduces a seven-step algorithm for objective physical activity measurement using accelerometry-based monitors. It provides best practice guidelines for data collection and processing to improve research consistency.

Area of Science:

Biomedical Engineering
Exercise Science
Public Health

Background:

Objective measurement of physical activity using wearable monitors lacks standardized guidelines.
Accelerometry-based activity monitors are widely used but require consistent data processing protocols.
Variability in data collection and processing can affect the reliability and comparability of physical activity research.

Purpose of the Study:

To present a standardized algorithm for collecting, processing, and reporting physical activity data from accelerometry-based monitors.
To establish best practice recommendations for enhancing the objectivity and consistency of physical activity research.
To facilitate better understanding and comparability of physical activity outcome variables across studies.

Main Methods:

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A seven-step algorithm is proposed, divided into three phases: Precollection, Data Collection, and Postcollection.
Precollection Phase: Defining population, activity type, outcome variables, and epoch duration; selecting monitors and wear-time/location.
Postcollection Phase: Data quality control, calibration, summarization, and generation of outcome variables (time, energy expenditure, movement type).

Main Results:

The algorithm provides a linear series of steps for comprehensive data handling.
It emphasizes full disclosure of each algorithmic step in research reporting.
The proposed method aims to improve the understanding of interactions between methodology and monitor selection.

Conclusions:

Adherence to the proposed algorithm and full disclosure of methods will enhance the quality and comparability of physical activity research.
This standardization is crucial for researchers to relate their findings to the existing literature.
The algorithm serves as a best practice guide for consistent and objective physical activity assessment.