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A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

Published on: April 21, 2017

Accelerometer use in a physical activity intervention trial.

Melissa A Napolitano¹, Kelley E Borradaile, Beth A Lewis

¹Temple University, Center for Obesity Research and Education, 3223 N Broad St Suite 175, Philadelphia, PA 19140, United States. napolita@temple.edu

Contemporary Clinical Trials

|August 21, 2010

Summary

This summary is machine-generated.

Accelerometers show modest agreement with self-reports for measuring physical activity (PA) in intervention trials. Best practices are crucial for accurate accelerometer data in clinical research.

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Area of Science:

Exercise Physiology
Biomedical Engineering
Clinical Trials

Background:

Physical activity (PA) measurement is crucial for intervention trials.
Accelerometers are increasingly used but require validation against other methods.
Best practice recommendations for accelerometer use in trials are needed.

Purpose of the Study:

To evaluate the concordance of accelerometer (ActiGraph) data with self-report measures and fitness variables in a PA intervention trial.
To assess the sensitivity of accelerometer data in detecting intervention effects on PA.
To provide recommendations for optimal accelerometer use in clinical trials.

Main Methods:

A subsample of healthy, sedentary adults in a PA intervention trial wore ActiGraph monitors.
ActiGraph data were compared with weekly recall, monthly log, and estimated VO(2)max.
Intervention effects on PA were analyzed using ActiGraph data at 6 and 12 months.

Main Results:

Correlations between ActiGraph and PA recall for moderate-to-vigorous PA ranged from 0.16-0.48.
Correlations between ActiGraph and estimated VO(2)max ranged from 0.15-0.45.
ActiGraph detected a significant increase in PA at 6 months but not 12 months in the intervention group.

Conclusions:

Accelerometers demonstrate modest concordance with self-report and fitness measures.
Following best practice recommendations is vital for reliable accelerometer data in clinical trials.
Self-report measures remain valuable alongside accelerometry until further validation in clinical settings.