Lynne M Feehan1, Charles H Goldsmith2, April Y F Leung3, Linda C Li1. 1. Arthritis Research Canada, Richmond; Department of Physical Therapy, University of British Columbia, Vancouver. 2. Arthritis Research Canada, Richmond; Faculty of Health Sciences, Simon Fraser University, Burnaby, B.C. 3. Arthritis Research Canada, Richmond.
Abstract
Purpose: To compare the ability of SenseWear Mini (SWm) and Actigraph GT3X (AG3) accelerometers to differentiate between healthy adults' observed sedentary and light activities in a laboratory setting. Methods: The 22 participants (15 women, 7 men), ages 19 to 72 years, wore SWm and AG3 monitors and performed five sedentary and four light activities for 5 minutes each while observed in a laboratory setting. Performance was examined through comparisons of accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Correct identification of both types of activities was examined using area under the receiver operating characteristic curve (AUC). Results: Both monitors demonstrated excellent ability to identify sedentary activities (sensitivity>0.89). The SWm monitor was better at identifying light activities (specificity 0.61-0.71) than the AG3 monitor (specificity 0.27-0.47) and thus also showed a greater ability to correctly identify both sedentary and light activities (SWm AUC 0.84; AG3 AUC 0.62-0.73). Conclusions: SWm may be a more suitable monitor for detecting time spent in sedentary and light-intensity activities. This finding has clinical and research relevance for evaluation of time spent in lower intensity physical activities by sedentary adults.
Purpose: To compare the ability of SenseWear Mini (SWm) and Actigraph GT3X (AG3) accelerometers to differentiate between healthy adults' observed sedentary and light activities in a laboratory setting. Methods: The 22 participants (15 women, 7 men), ages 19 to 72 years, wore SWm and AG3 monitors and performed five sedentary and four light activities for 5 minutes each while observed in a laboratory setting. Performance was examined through comparisons of accuracy, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Correct identification of both types of activities was examined using area under the receiver operating characteristic curve (AUC). Results: Both monitors demonstrated excellent ability to identify sedentary activities (sensitivity>0.89). The SWm monitor was better at identifying light activities (specificity 0.61-0.71) than the AG3 monitor (specificity 0.27-0.47) and thus also showed a greater ability to correctly identify both sedentary and light activities (SWm AUC 0.84; AG3 AUC 0.62-0.73). Conclusions: SWm may be a more suitable monitor for detecting time spent in sedentary and light-intensity activities. This finding has clinical and research relevance for evaluation of time spent in lower intensity physical activities by sedentary adults.
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