Date of Degree
Access restricted until 01/31/2020
PhD (Doctor of Philosophy)
Health and Sport Studies
Janz, Kathleen F
First Committee Member
Carr, Lucas J
Second Committee Member
Burns, Trudy L
Third Committee Member
Pierce, Gary L
Fourth Committee Member
Levy, Steven M
PURPOSE: To understand the influences of mechanical loading on bone adaptation, the ground reaction force (GRF) applied to the bone must be quantified. The use of force plates in a lab setting is the accepted method for quantifying GRFs; however, this is not feasible in free-living situations. Recent developments in accelerometer technology may provide the ability to evaluate the effects of mechanical loading on bone outside of laboratory settings. The purpose of this project was to validate an accelerometer for the measurement of mechanical loading by comparing its output against GRFs.
METHODS: Male and female participants (n = 20 males, 20 females; 18 to 49 yr) completed 10 repetitions of 9 common everyday movements (stand, walk, jog, run, 15 cm jump, step down from curb, drop down from curb, forward hop, and side hop) on a force plate with an accelerometer worn on their right hip. Then, a subset (n = 5 males, 5 females) wore an accelerometer on their right hip and played basketball, volleyball, and dodgeball as a group. Finally, all 40 participants wore an accelerometer home for 7 days. All activities were organized into derived activity categories labeled as low-, moderate-, and high-mechanical-load-intensity and used with 59 possible accelerometer variables to predict mechanical load. Models were fit using the randomForest package in R. Model performance (coefficient of determination [R2] and median absolute error) was evaluated using cross-validation.
RESULTS: The percentage of variation mechanical load intensity explained by the models ranged from 0.27 to 0.78 with median absolute errors ranging from 0.20 to 0.49. The model with R2 = 0.78 contained the known activity categories and the accelerometer variables, but this is not realistic for free-living situations where activity categories will not be known. The two free-living models with the highest R2 values included derived activity categories and accelerometer variables, and estimated, on average, 21.1 and 20.7 hours per day in low-intensity, 1.6 and 1.7 hours per day in moderate-intensity, and 0.0 and 0.5 hours per day in high-intensity osteogenic activity, respectively.
CONCLUSION: It is assumed that higher intensity activities (i.e., jumping vs. jogging) result in higher GRF values, but depending on the actual execution of the movement, this is not always the case. This research demonstrated that models containing the accelerometer variables performed better in predicting GRF than those containing only the derived activity categories. This supports the hypothesis that accelerometers provide valuable objective information when evaluating mechanical loading on bone.
accelerometer, Actigraph, bone remodeling, mechanical loading, physical activity
xii, 167 pages
Includes bibliographical references.
Copyright © 2017 Shelby L. Francis
Francis, Shelby L.. "Using an accelerometer to predict mechanical load of physical activities in young and middle-aged adults." PhD (Doctor of Philosophy) thesis, University of Iowa, 2017.