Portable Global Positioning Units to Complement Accelerometry-Based Physical Activity Monitors
ABSTRACT This study examines the usefulness of complementing accelerometry-based physical activity measurement with spatial data from portable global positioning system (GPS) units to determine where physical activity occurs.
First, using the geographic distribution of data points and Bland-Altman plots, we examined GPS units' validity and interunit reliability by measuring the distance to a geodetic point. We also assessed interunit reliability by comparing GPS data collected in three built environment contexts. Second, we conducted a pilot study in which 35 participants wore GPS units and accelerometers in free-living conditions for 3 d. Moderate and vigorous physical activity (MVPA) bouts were matched to GPS data. We classified each bout as occurring inside or outside the participant's home neighborhood. Using unpaired t-tests and Fisher's exact tests, we compared neighborhood attributes for participants having the majority of MVPA bouts within their home neighborhood, relative to those with most bouts away from their home neighborhood.
Average distance from each unit to the geodetic point was 3.02 m (SD 2.51). Average bias among units using Bland-Altman plots was 0.90 m, ranging from -0.22 to 1.86 m, within the limits of agreement. For interunit reliability in the built environment contexts, the mean distance difference among units ranged between 10.7 m (SD 11.9) and 20.1 m (SD 21.8). For the pilot study involving participants, GPS data were available for 59.3% of all bouts (67% of MVPA time), of which 46% were in the participants' neighborhood. Participants obtaining most of their MVPA in their neighborhoods tend to live in areas with higher population density, housing unit density, street connectivity, and more public parks.
Data recorded by portable GPS units is sufficiently precise to track participants' movements. Successful matching of activity monitor and locational data suggests GPS is a promising tool for complementing accelerometry-based physical activity measures. Our pilot analysis shows evidence that the relationship between environment and activity can be clarified by examining where physical activity occurs.
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- "Positional data were recorded every ten seconds using a GPS receiver (GPS; Garmin Foretrex 201) . Participants wore the GPS receiver between the end of school and bedtime on four consecutive school days. "
ABSTRACT: Understanding how the determinants of behaviour vary by context may support the design of interventions aiming to increase physical activity. Such factors include independent mobility, time outdoors and the availability of other children. At present little is known about who children spend their time with after school, how this relates to time spent indoors or outdoors and activity in these locations. This study aimed to quantify who children spend their time with when indoors or outdoors and associations with moderate to vigorous physical activity (MVPA). Participants were 427 children aged 10-11 from Bristol, UK. Physical activity was recorded using an accelerometer (Actigraph GT1M) and matched to Global Positioning System receiver (Garmin Foretrex 201) data to differentiate indoor and outdoor location. Children self-reported who they spent time with after school until bed-time using a diary. Each 10 second epoch was coded as indoors or outdoors and for 'who with' (alone, friend, brother/sister, mum/dad, other grown-up) creating 10 possible physical activity contexts. Time spent and MVPA were summarised for each context. Associations between time spent in the different contexts and MVPA were examined using multiple linear regression adjusting for daylight, age, deprivation and standardised body mass index. During the after school period, children were most often with their mum/dad or alone, especially when indoors. When outdoors more time was spent with friends (girls: 32.1%; boys: 28.6%) than other people or alone. Regression analyses suggested hours outdoors with friends were positively associated with minutes of MVPA for girls (beta-coefficient [95% CI]: 17.4 [4.47, 30.24]) and boys (17.53 [2.76, 32.31]). Being outdoors with brother/sister was associated with MVPA for girls (21.2 [14.17, 28.25]) but not boys. Weaker associations were observed for time indoors with friends (girls: 4.61 [1.37, 7.85]; boys: (7.42 [2.99, 11.85]) and other adults (girls: 5.33 [2.95, 7.71]; boys: (4.44 [1.98, 6.90]). Time spent alone was not associated with MVPA regardless of gender or indoor/outdoor location. Time spent outdoors with other children is an important source of MVPA after school. Interventions to increase physical activity may benefit from fostering friendship groups and limiting the time children spend alone.International Journal of Behavioral Nutrition and Physical Activity 03/2014; 11(1):45. DOI:10.1186/1479-5868-11-45 · 4.11 Impact Factor
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- "Different methods have been used by various researchers to test the dynamic accuracy of many different GPS devices. Rodriguez et al. (10) used the average location recorded from multiple units of the same device (Garmin Foretrex 201) to assess accuracy under a variety of free-living scenarios. They found that the average distance between each unit and the average of five other identical units was 10.7 ± 11.9 m in open space scenarios and 20.1 ± 21.8 m in clustered development scenarios (10). "
ABSTRACT: The emergence of portable global positioning system (GPS) receivers over the last 10 years has provided researchers with a means to objectively assess spatial position in free-living conditions. However, the use of GPS in free-living conditions is not without challenges and the aim of this study was to test the dynamic accuracy of a portable GPS device under real-world environmental conditions, for four modes of transport, and using three data collection intervals. We selected four routes on different bearings, passing through a variation of environmental conditions in the City of Copenhagen, Denmark, to test the dynamic accuracy of the Qstarz BT-Q1000XT GPS device. Each route consisted of a walk, bicycle, and vehicle lane in each direction. The actual width of each walking, cycling, and vehicle lane was digitized as accurately as possible using ultra-high-resolution aerial photographs as background. For each trip, we calculated the percentage that actually fell within the lane polygon, and within the 2.5, 5, and 10 m buffers respectively, as well as the mean and median error in meters. Our results showed that 49.6% of all ≈68,000 GPS points fell within 2.5 m of the expected location, 78.7% fell within 10 m and the median error was 2.9 m. The median error during walking trips was 3.9, 2.0 m for bicycle trips, 1.5 m for bus, and 0.5 m for car. The different area types showed considerable variation in the median error: 0.7 m in open areas, 2.6 m in half-open areas, and 5.2 m in urban canyons. The dynamic spatial accuracy of the tested device is not perfect, but we feel that it is within acceptable limits for larger population studies. Longer recording periods, for a larger population are likely to reduce the potentially negative effects of measurement inaccuracy. Furthermore, special care should be taken when the environment in which the study takes place could compromise the GPS signal.Frontiers in Public Health 03/2014; 2:21. DOI:10.3389/fpubh.2014.00021
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- "Missing data are even more common with GPS monitors, which encounter signal drop inside some buildings or dense urban areas and battery drain after 24 h of use (12, 13). GPS data availability ranges from 11 to 60% of all possible records in recent studies (14–16) with user error as a significant cause of missing data in adolescents (17). A particular concern is that these data are not missing at random (e.g., Actigraph removed during a soccer game), which can result in biased activity estimates from objective monitors. "
ABSTRACT: Introduction: Despite the known advantages of objective physical activity monitors (e.g., accelerometers), these devices have high rates of non-wear, which leads to missing data. Objective activity monitors are also unable to capture valuable contextual information about behavior. Adolescents recruited into physical activity surveillance and intervention studies will increasingly have smartphones, which are miniature computers with built-in motion sensors. Methods: This paper describes the design and development of a smartphone application (“app”) called Mobile Teen that combines objective and self-report assessment strategies through (1) sensor-informed context-sensitive ecological momentary assessment (CS-EMA) and (2) sensor-assisted end-of-day recall. Results: The Mobile Teen app uses the mobile phone’s built-in motion sensor to automatically detect likely bouts of phone non-wear, sedentary behavior, and physical activity. The app then uses transitions between these inferred states to trigger CS-EMA self-report surveys measuring the type, purpose, and context of activity in real-time. The end of the day recall component of the Mobile Teen app allows users to interactively review and label their own physical activity data each evening using visual cues from automatically detected major activity transitions from the phone’s built-in motion sensors. Major activity transitions are identified by the app, which cues the user to label that “chunk,” or period, of time using activity categories. Conclusion: Sensor-driven CS-EMA and end-of-day recall smartphone apps can be used to augment physical activity data collected by objective activity monitors, filling in gaps during non-wear bouts and providing additional real-time data on environmental, social, and emotional correlates of behavior. Smartphone apps such as these have potential for affordable deployment in large-scale epidemiological and intervention studies.Frontiers in Public Health 02/2014; 2:12. DOI:10.3389/fpubh.2014.00012