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- Maddison, Ralph, et al.
(författare)
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Quantifying Human Movement Using the Movn Smartphone App : Validation and Field Study
- 2017
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Ingår i: JMIR mhealth and uhealth. - Toronto : J M I R Publications, Inc.. - 2291-5222. ; 5:8
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Tidskriftsartikel (refereegranskat)abstract
- Background: The 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. Objective: The objective of this study was to examine the validity of the Movn smartphone app (Moving Analytics) for collecting PA and human movement data. Methods: The 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. Results: A 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<.001). The absolute magnitude of criterion biases increased as a function of locomotive speed (F1,4=7.54, P<.001) but was relatively consistent for the convergent comparison (F1,4=1.26, P<.29). Furthermore, 95% limits of agreement were consistent for criterion and convergent biases, and EE from Movn was strongly correlated with both reference measures (criterion r=.91, convergent r=.92, both P<.001). Movn overestimated EE during free-living activities (bias=1.00 [0.98-1.02] kcal/min, t(6123)=101.49, P<.001), and biases were larger during high-intensity activities (F-3,F-6120=1550.51, P<.001). In addition, 95% limits of agreement for convergent biases were heterogeneous across free-living activity intensity levels, but Movn and ActiGraph measures were strongly correlated (r=.87, P<.001). Integration of GPS and accelerometer data within a geographic information system (GIS) enabled creation of individual temporospatial maps. Conclusions: The Movn smartphone app can provide valid passive measurement of EE and can enrich these data with contextualizing temporospatial information. Although enhanced understanding of geographic and temporal variation in human movement patterns could inform intervention development, it also presents challenges for data processing and analytics.
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| 2. |
- Tudor-Locke, Catrine, et al.
(författare)
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How many steps/day are enough? for children and adolescents.
- 2011
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Ingår i: The international journal of behavioral nutrition and physical activity. - : Springer Science and Business Media LLC. - 1479-5868. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Worldwide, public health physical activity guidelines include special emphasis on populations of children (typically 6-11 years) and adolescents (typically 12-19 years). Existing guidelines are commonly expressed in terms of frequency, time, and intensity of behaviour. However, the simple step output from both accelerometers and pedometers is gaining increased credibility in research and practice as a reasonable approximation of daily ambulatory physical activity volume. Therefore, the purpose of this article is to review existing child and adolescent objectively monitored step-defined physical activity literature to provide researchers, practitioners, and lay people who use accelerometers and pedometers with evidence-based translations of these public health guidelines in terms of steps/day. In terms of normative data (i.e., expected values), the updated international literature indicates that we can expect 1) among children, boys to average 12,000 to 16,000 steps/day and girls to average 10,000 to 13,000 steps/day; and, 2) adolescents to steadily decrease steps/day until approximately 8,000-9,000 steps/day are observed in 18-year olds. Controlled studies of cadence show that continuous MVPA walking produces 3,300-3,500 steps in 30 minutes or 6,600-7,000 steps in 60 minutes in 10-15 year olds. Limited evidence suggests that a total daily physical activity volume of 10,000-14,000 steps/day is associated with 60-100 minutes of MVPA in preschool children (approximately 4-6 years of age). Across studies, 60 minutes of MVPA in primary/elementary school children appears to be achieved, on average, within a total volume of 13,000 to 15,000 steps/day in boys and 11,000 to 12,000 steps/day in girls. For adolescents (both boys and girls), 10,000 to 11,700 may be associated with 60 minutes of MVPA. Translations of time- and intensity-based guidelines may be higher than existing normative data (e.g., in adolescents) and therefore will be more difficult to achieve (but not impossible nor contraindicated). Recommendations are preliminary and further research is needed to confirm and extend values for measured cadences, associated speeds, and MET values in young people; continue to accumulate normative data (expected values) for both steps/day and MVPA across ages and populations; and, conduct longitudinal and intervention studies in children and adolescents required to inform the shape of step-defined physical activity dose-response curves associated with various health parameters.
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