Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study

Autor: Maddison, Ralph, Gemming, Luke, Monedero, Javier, Bolger, Linda, Belton, Sarahjane, Issartel, Johann, Marsh, Samantha, Direito, Artur, Solenhill, Madeleine, Zhao, Jinfeng, Exeter, Daniel John, Vathsangam, Harshvardhan, Rawstorn, Jonathan Charles
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: JMIR mHealth and uHealth, Vol 5, Iss 8, p e122 (2017)
Druh dokumentu: article
ISSN: 2291-5222
DOI: 10.2196/mhealth.7167
Popis: BackgroundThe use of embedded smartphone sensors offers opportunities to measure physical activity (PA) and human movement. Big data—which includes billions of digital traces—offers scientists a new lens to examine PA in fine-grained detail and allows us to track people’s geocoded movement patterns to determine their interaction with the environment. ObjectiveThe objective of this study was to examine the validity of the Movn smartphone app (Moving Analytics) for collecting PA and human movement data. MethodsThe criterion and convergent validity of the Movn smartphone app for estimating energy expenditure (EE) were assessed in both laboratory and free-living settings, compared with indirect calorimetry (criterion reference) and a stand-alone accelerometer that is commonly used in PA research (GT1m, ActiGraph Corp, convergent reference). A supporting cross-validation study assessed the consistency of activity data when collected across different smartphone devices. Global positioning system (GPS) and accelerometer data were integrated with geographical information software to demonstrate the feasibility of geospatial analysis of human movement. ResultsA total of 21 participants contributed to linear regression analysis to estimate EE from Movn activity counts (standard error of estimation [SEE]=1.94 kcal/min). The equation was cross-validated in an independent sample (N=42, SEE=1.10 kcal/min). During laboratory-based treadmill exercise, EE from Movn was comparable to calorimetry (bias=0.36 [−0.07 to 0.78] kcal/min, t82=1.66, P=.10) but overestimated as compared with the ActiGraph accelerometer (bias=0.93 [0.58-1.29] kcal/min, t89=5.27, P
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