Grant Number:	5R01CA215318-05 Interpret this number
Primary Investigator:	Strath, Scott
Organization:	University Of Wisconsin Milwaukee
Project Title:	Calibrating Free-Living Physical Activity Characteristics Across Functionally-Limited Populations Using Machine-Learned Accelerometer Approaches
Fiscal Year:	2021

PROJECT SUMMARY/ ABSTRACT One in 5 U.S. adults are thought to be living with a disability/impairment, a complex and multifaceted condition affecting movement patterns with related medical care costs exceeding $300 billion annually. Precise and accurate assessment of physical activity (PA) and sedentary behavior (SB) in individuals with disabiliy/ impairment is essential to accurately measure PA/SB prevalence rates and effectiveness of behavioral based PA/SB interventions, and to fully elucidate PA/SB dose-response health relationships. Scientific progress has been made in this area with advanced analytics and data processing techniques applied to wearable accelerometers from laboratory calibration studies. There is a scientific need to extend calibration studies from fixed-duration laboratory simulated activities of daily living to free-living calibrations with natural observation and accelerometer algorithm training and validation. The aims of this proposal fill this essential scientific knowledge gap. The specific aims are: 1) To evaluate and refine machine-learned algorithms to predict energy cost and activity type during a 24-hr respiratory calorimeter stay; 2) To validate machine-learned accelerometer algorithms with field-derived, video-recorded direct observation; and 3) To validate machine-learned algorithms using the doubly labeled water technique. Our highly qualified research team will address the above aims by using brief translatable functional tests to cluster movement-impaired populations into groups of healthy, upper-body impairment, lower-body impairment, and upper- and lower-body impairment. Best practice free- living calibration protocols will then be used to train, refine, and evaluate functional clustered-specific accelerometer algorithms for predicting activity energy cost, activity type, activity transitions, and activity domain. The results of these proposed studies will for the first time provide an innovative and translatable approach to categorize and assess free-living PA/SB in persons with disability and movement impairment. 





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