scholarly journals Combining global positioning system and accelerometer data to determine the locations of physical activity in children

2012 ◽  
Vol 6 (2) ◽  
pp. 263 ◽  
Author(s):  
Nicolas M. Oreskovic ◽  
Jeff Blossom ◽  
Alison E. Field ◽  
Sylvia R. Chiang ◽  
Jonathan P. Winickoff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Global Positioning System ◽  
Positioning System ◽  
Accelerometer Data ◽  
Global Positioning

scholarly journals Associations between time spent in green areas and physical activity among late middle-aged adults

2016 ◽  
Vol 11 (3) ◽  
Author(s):  
Bart Dewulf ◽  
Tijs Neutens ◽  
Delfien Van Dyck ◽  
Ilse De Bourdeaudhuij ◽  
Steven Broekx ◽  
...  
Keyword(s):  
Physical Activity ◽  
Global Positioning System ◽  
Individual Characteristics ◽  
Positioning System ◽  
Accelerometer Data ◽  
Middle Aged ◽  
Physically Active ◽  
Global Positioning ◽  
Green Areas ◽  
Middle Aged Adults

Physical activity is an important facilitator for health and wellbeing, especially for late middle-aged adults, who are more susceptible to cardiovascular diseases. Physical activity performed in green areas is supposed to be particularly beneficial, so we studied whether late middle- aged adults are more active in green areas than in non-green areas and how this is influenced by individual characteristics and the level of neighbourhood greenness. We tracked 180 late middle-aged (58 to 65 years) adults using global positioning system and accelerometer data to know whether and where they were sedentary or active. These data were combined with information on land use to obtain information on the greenness of sedentary and active hotspots. We found that late middle-aged adults are more physically active when spending more time in green areas than in non-green areas. Spending more time at home and in non-green areas was found to be associated with more sedentary behaviour. Time spent in non-green areas was found to be related to more moderate-to-vigorous physical activity (MVPA) for males and to less MVPA for females. The positive association between time spent in green areas and MVPA was the strongest for highly educated people and for those living in a green neighbourhood. This study shows that the combined use of global positioning system and accelerometer data facilitates understanding of where people are sedentary or physically active, which can help policy makers encourage activity in this age cohort.

A Multicomponent Schoolyard Intervention Targeting Children’s Recess Physical Activity and Sedentary Behavior: Effects After 1 Year

2017 ◽  
Vol 14 (11) ◽  
pp. 866-875 ◽  
Author(s):  
Dave H.H. Van Kann ◽  
Sanne I. de Vries ◽  
Jasper Schipperijn ◽  
Nanne K. de Vries ◽  
Maria W.J. Jansen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Linear Regression ◽  
Sedentary Behavior ◽  
Global Positioning System ◽  
Primary Schools ◽  
Positioning System ◽  
Accelerometer Data ◽  
Regression Analyses ◽  
Global Positioning ◽  
Quasi Experimental

Background: The aim of the study was to test the 12-month effects of a multicomponent physical activity (PA) intervention at schoolyards on morning recess PA levels of sixth- and seventh-grade children in primary schools, using accelerometry and additional global positioning system data. Methods: A quasi-experimental study design was used with 20 paired intervention and control schools. Global positioning system confirmatory analyses were applied to validate attendance at schoolyards during recess. Accelerometer data from 376 children from 7 pairs of schools were included in the final analyses. Pooled intervention effectiveness was tested by multilevel linear regression analyses, whereas effectiveness of intervention components was tested by multivariate linear regression analyses. Results: Children exposed to the multicomponent intervention increased their time spent in light PA (+5.9%) during recess. No pooled effects on moderate to vigorous PA were found. In-depth analyses of intervention components showed that physical schoolyard interventions particularly predicted a decrease in time spent in sedentary behavior during recess at follow-up. Intervention intensity and the school’s commitment to the project strengthened this effect. Conclusions: The multicomponent schoolyard PA intervention was effective in making children spend a larger proportion of recess time in light PA, which was most likely the result of a shift from sedentary behavior to light PA.

Prediction of Activity Mode with Global Positioning System and Accelerometer Data

2008 ◽  
Vol 40 (5) ◽  
pp. 972-978 ◽  
Author(s):  
PHILIP J. TROPED ◽  
MARCELO S. OLIVEIRA ◽  
CHARLES E. MATTHEWS ◽  
ELLEN K. CROMLEY ◽  
STEVEN J. MELLY ◽  
...  
Keyword(s):  
Global Positioning System ◽  
Positioning System ◽  
Accelerometer Data ◽  
Global Positioning ◽  
Activity Mode

scholarly journals Concurrent Measurement of Global Positioning System and Event-Based Physical Activity Data: A Methodological Framework for Integration

2020 ◽  
pp. 1-14
Author(s):  
Anna M.J. Iveson ◽  
Malcolm H. Granat ◽  
Brian M. Ellis ◽  
Philippa M. Dall
Keyword(s):  
Physical Activity ◽  
Outcome Measures ◽  
Global Positioning System ◽  
Gps Data ◽  
Positioning System ◽  
Activity Data ◽  
Data Set ◽  
Physical Activity Data ◽  
Global Positioning ◽  
Event Based

Objective: Global positioning system (GPS) data can add context to physical activity data and have previously been integrated with epoch-based physical activity data. The current study aimed to develop a framework for integrating GPS data and event-based physical activity data (suitable for assessing patterns of behavior). Methods: A convenience data set of concurrent GPS (AMOD) and physical activity (activPAL) data were collected from 69 adults. The GPS data were (semi)regularly sampled every 5 s. The physical activity data output was presented as walking events, which are continuous periods of walking with a time-stamped start time and duration (to nearest 0.1 s). The GPS outcome measures and the potential correspondence of their timing with walking events were identified and a framework was developed describing data integration for each combination of GPS outcome and walking event correspondence. Results: The GPS outcome measures were categorized as those deriving from a single GPS point (e.g., location) or from the difference between successive GPS points (e.g., distance), and could be categorical, scale, or rate outcomes. Walking events were categorized as having zero (13% of walking events, 3% of walking duration), or one or more (52% of walking events, 75% of walking duration) GPS points occurring during the event. Additionally, some walking events did not have GPS points suitably close to allow calculation of outcome measures (31% of walking events, 22% of walking duration). The framework required different integration approaches for each GPS outcome type, and walking events containing zero or more than one GPS points.

scholarly journals Global Positioning System Derived Performance Measures Are Responsive Indicators of Physical Activity, Disease and the Success of Clinical Treatments in Domestic Dogs

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0117094 ◽  
Author(s):  
Elizabeth A. Bruno ◽  
James W. Guthrie ◽  
Stephen A. Ellwood ◽  
Richard J. Mellanby ◽  
Dylan N. Clements
Keyword(s):  
Physical Activity ◽  
Performance Measures ◽  
Global Positioning System ◽  
Domestic Dogs ◽  
Positioning System ◽  
Global Positioning

scholarly journals Accelerometer and GPS Analysis of Trail Use and Associations With Physical Activity

2018 ◽  
Vol 15 (7) ◽  
pp. 523-530 ◽  
Author(s):  
Kosuke Tamura ◽  
Jeffrey S. Wilson ◽  
Robin C. Puett ◽  
David B. Klenosky ◽  
William A. Harper ◽  
...  
Keyword(s):  
Physical Activity ◽  
Light Intensity ◽  
Global Positioning System ◽  
Moderate Intensity ◽  
Gps Data ◽  
Accelerometer Data ◽  
Trail Use ◽  
Concurrent Use ◽  
Global Positioning ◽  
Vigorous Intensity

Background: Concurrent use of accelerometers and global positioning system (GPS) data can be used to quantify physical activity (PA) occurring on trails. This study examined associations of trail use with PA and sedentary behavior (SB) and quantified on trail PA using a combination of accelerometer and GPS data. Methods: Adults (N = 142) wore accelerometer and GPS units for 1–4 days. Trail use was defined as a minimum of 2 consecutive minutes occurring on a trail, based on GPS data. We examined associations between trail use and PA and SB. On trail minutes of light-intensity, moderate-intensity, and vigorous-intensity PA, and SB were quantified in 2 ways, using accelerometer counts only and with a combination of GPS speed and accelerometer data. Results: Trail use was positively associated with total PA, moderate-intensity PA, and light-intensity PA (P < .05). On trail vigorous-intensity PA minutes were 346% higher when classified with the combination versus accelerometer only. Light-intensity PA, moderate-intensity PA, and SB minutes were 15%, 91%, and 85% lower with the combination, respectively. Conclusions: Adult trail users accumulated more PA on trail use days than on nontrail use days, indicating the importance of these facilities for supporting regular PA. The combination of GPS and accelerometer data for quantifying on trail activity may be more accurate than accelerometer data alone and is useful for classifying intensity of activities such as bicycling.

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