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Open AccessArticle

Validation of the VitaBit Sit–Stand Tracker: Detecting Sitting, Standing, and Activity Patterns

1
Department of Work and Social Psychology, Faculty of Psychology and Neuroscience, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
2
Department of Human Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 877; https://doi.org/10.3390/s18030877
Received: 23 February 2018 / Revised: 13 March 2018 / Accepted: 14 March 2018 / Published: 15 March 2018
Sedentary behavior (SB) has detrimental consequences and cannot be compensated for through moderate-to-vigorous physical activity (PA). In order to understand and mitigate SB, tools for measuring and monitoring SB are essential. While current direct-to-customer wearables focus on PA, the VitaBit validated in this study was developed to focus on SB. It was tested in a laboratory and in a free-living condition, comparing it to direct observation and to a current best-practice device, the ActiGraph, on a minute-by-minute basis. In the laboratory, the VitaBit yielded specificity and negative predictive rates (NPR) of above 91.2% for sitting and standing, while sensitivity and precision ranged from 74.6% to 85.7%. For walking, all performance values exceeded 97.3%. In the free-living condition, the device revealed performance of over 72.6% for sitting with the ActiGraph as criterion. While sensitivity and precision for standing and walking ranged from 48.2% to 68.7%, specificity and NPR exceeded 83.9%. According to the laboratory findings, high performance for sitting, standing, and walking makes the VitaBit eligible for SB monitoring. As the results are not transferrable to daily life activities, a direct observation study in a free-living setting is recommended. View Full-Text
Keywords: sedentary behavior; VitaBit; accelerometer; validation; sensitivity; specificity; positive predictive rate; negative predictive rate sedentary behavior; VitaBit; accelerometer; validation; sensitivity; specificity; positive predictive rate; negative predictive rate
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MDPI and ACS Style

Berninger, N.M.; Ten Hoor, G.A.; Plasqui, G. Validation of the VitaBit Sit–Stand Tracker: Detecting Sitting, Standing, and Activity Patterns. Sensors 2018, 18, 877. https://doi.org/10.3390/s18030877

AMA Style

Berninger NM, Ten Hoor GA, Plasqui G. Validation of the VitaBit Sit–Stand Tracker: Detecting Sitting, Standing, and Activity Patterns. Sensors. 2018; 18(3):877. https://doi.org/10.3390/s18030877

Chicago/Turabian Style

Berninger, Nathalie M.; Ten Hoor, Gill A.; Plasqui, Guy. 2018. "Validation of the VitaBit Sit–Stand Tracker: Detecting Sitting, Standing, and Activity Patterns" Sensors 18, no. 3: 877. https://doi.org/10.3390/s18030877

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