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Chelsea Steel, Carolina Bejarano and Jordan A. Carlson

Concurrent use of multiple person-worn sensors, such as combining data from Global Positioning Systems (GPS) trackers and accelerometers, is becoming more common in field-based physical activity research. The use of GPS trackers combined with accelerometers has been particularly useful in the

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Kosuke Tamura, Jeffrey S. Wilson, Robin C. Puett, David B. Klenosky, William A. Harper and Philip J. Troped

accelerometers and global positioning system (GPS) units can be used to quantify PA occurring on trails and thereby provide a better understanding of how community trails can support regular PA. 23 , 24 To date, researchers have concurrently used these devices to objectively assess how much PA occurs at home

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Levi Frehlich, Christine Friedenreich, Alberto Nettel-Aguirre, Jasper Schipperijn and Gavin R. McCormack

measure of geographical location. Recent studies have captured location specific physical activity through the use of Global Position Systems (GPS) monitors usually linked via time stamp with accelerometer data ( Jansen et al., 2018 ; Troped, Wilson, Matthews, Cromley, & Melly, 2010 ). GPS linked

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Sandra C. Webber and Michelle M. Porter

This exploratory study examined the feasibility of using Garmin global positioning system (GPS) watches and ActiGraph accelerometers to monitor walking and other aspects of community mobility in older adults. After accuracy at slow walking speeds was initially determined, 20 older adults (74.4 ± 4.2 yr) wore the devices for 1 day. Steps, distances, and speeds (on foot and in vehicle) were determined. GPS data acquisition varied from 43 min to over 12 hr, with 55% of participants having more than 8 hr between initial and final data-collection points. When GPS data were acquired without interruptions, detailed mobility information was obtained regarding the timing, distances covered, and speeds reached during trips away from home. Although GPS and accelerometry technology offer promise for monitoring community mobility patterns, new GPS solutions are required that allow for data collection over an extended period of time between indoor and outdoor environments.

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Daniel A. Rodriguez, Gi-Hyoug Cho, John P. Elder, Terry L. Conway, Kelly R. Evenson, Bonnie Ghosh-Dastidar, Elizabeth Shay, Deborah Cohen, Sara Veblen-Mortenson, Julie Pickrell and Leslie Lytle

Background:

Studies that have combined accelerometers and global positioning systems (GPS) to identify walking have done so in carefully controlled conditions. This study tested algorithms for identifying walking trips from accelerometer and GPS data in free-living conditions. The study also assessed the accuracy of the locations where walking occurred compared with what participants reported in a diary.

Methods:

A convenience sample of high school females was recruited (N = 42) in 2007. Participants wore a GPS unit and an accelerometer, and recorded their out-of-school travel for 6 days. Split-sample validation was used to examine agreement in the daily and total number of walking trips with Kappa statistics and count regression models, while agreement in locations visited by walking was examined with geographic information systems.

Results:

Agreement varied based on the parameters of the algorithm, with algorithms exhibiting moderate to substantial agreement with self-reported daily (Kappa = 0.33−0.48) and weekly (Kappa = 0.41−0.64) walking trips. Comparison of reported locations reached by walking and GPS data suggest that reported locations are accurate.

Conclusions:

The use of GPS and accelerometers is promising for assessing the number of walking trips and the walking locations of adolescent females.

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Melody Oliver, Hannah Badland, Suzanne Mavoa, Mitch J. Duncan and Scott Duncan

Background:

Global positioning systems (GPS), geographic information systems (GIS), and accelerometers are powerful tools to explain activity within a built environment, yet little integration of these tools has taken place. This study aimed to assess the feasibility of combining GPS, GIS, and accelerometry to understand transport-related physical activity (TPA) in adults.

Methods:

Forty adults wore an accelerometer and portable GPS unit over 7 consecutive days and completed a demographics questionnaire and 7-day travel log. Accelerometer and GPS data were extracted for commutes to/from workplace and integrated into a GIS database. GIS maps were generated to visually explore physical activity intensity, GPS speeds and routes traveled.

Results:

GPS, accelerometer, and survey data were collected for 37 participants. Loss of GPS data was substantial due to a range of methodological issues, such as low battery life, signal drop out, and participant noncompliance. Nonetheless, greater travel distances and significantly higher speeds were observed for motorized trips when compared with TPA.

Conclusions:

Pragmatic issues of using GPS monitoring to understand TPA behaviors and methodological recommendations for future research were identified. Although methodologically challenging, the combination of GPS monitoring, accelerometry and GIS technologies holds promise for understanding TPA within the built environment.

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Kathleen Meghan Wieters, Jun-Hyun Kim and Chanam Lee

Background:

Responding to the growing interest in the environmental influences on physical activity, and the concerns about the limitations of self-report data, this study evaluates Global Positioning System (GPS) units for measuring outdoor physical activity.

Methods:

Four GPS models were selected to test their accuracy related to adherence to an actual route walked, variations based on position of unit on user’s body, and variations against a known geodetic point. A qualitative assessment was performed using the following criteria: a) battery life, b) memory capacity, c) initial satellite signal acquisition time, d) ease of data transfer to other programs, e) wearability, f) ease of operation, g) suitability for specific study populations, and h) price.

Results and Conclusions:

The Garmin Forerunner provided the most accurate data for data points collected along a known route. Comparisons based on different body placement of units showed some variations. GlobalSat reported battery life of 24 hours, compared with 9–15 hours for the other units. The static test using ANOVA showed that the Garmin Foretrex’s data points compared with a geodetic point was significantly more accurate than the other 3 models. GPS units appear promising as a tool to capture objective data on outdoor physical activities.

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Dac Minh Tuan Nguyen, Virgile Lecoultre, Yoshiyuki Sunami and Yves Schutz

Background:

Physical activity (PA) and related energy expenditure (EE) is often assessed by means of a single technique. Because of inherent limitations, single techniques may not allow for an accurate assessment both PA and related EE. The aim of this study was to develop a model to accurately assess common PA types and durations and thus EE in free-living conditions, combining data from global positioning system (GPS) and 2 accelerometers.

Methods:

Forty-one volunteers participated in the study. First, a model was developed and adjusted to measured EE with a first group of subjects (Protocol I, n = 12) who performed 6 structured and supervised PA. Then, the model was validated over 2 experimental phases with 2 groups (n = 12 and n = 17) performing scheduled (Protocol I) and spontaneous common activities in real-life condition (Protocol II). Predicted EE was compared with actual EE as measured by portable indirect calorimetry.

Results:

In protocol I, performed PA types could be recognized with little error. The duration of each PA type could be predicted with an accuracy below 1 minute. Measured and predicted EE were strongly associated (r = .97, P < .001).

Conclusion:

Combining GPS and 2 accelerometers allows for an accurate assessment of PA and EE in free-living situations.

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Weimo Zhu, Zorica Nedovic-Budic, Robert B. Olshansky, Jed Marti, Yong Gao, Youngsik Park, Edward McAuley and Wojciech Chodzko-Zajko

Purpose:

To introduce Agent-Based Model (ABM) to physical activity (PA) research and, using data from a study of neighborhood walkability and walking behavior, to illustrate parameters for an ABM of walking behavior.

Method:

The concept, brief history, mechanism, major components, key steps, advantages, and limitations of ABM were first introduced. For illustration, 10 participants (age in years: mean = 68, SD = 8) were recruited from a walkable and a nonwalkable neighborhood. They wore AMP 331 triaxial accelerometers and GeoLogger GPA tracking devices for 21 days. Data were analyzed using conventional statistics and highresolution geographic image analysis, which focused on a) path length, b) path duration, c) number of GPS reporting points, and d) interaction between distances and time.

Results:

Average steps by subjects ranged from 1810−10,453 steps per day (mean = 6899, SD = 3823). No statistical difference in walking behavior was found between neighborhoods (Walkable = 6710 ± 2781, Nonwalkable = 7096 ± 4674). Three environment parameters (ie, sidewalk, crosswalk, and path) were identified for future ABM simulation.

Conclusion:

ABM should provide a better understanding of PA behavior’s interaction with the environment, as illustrated using a real-life example. PA field should take advantage of ABM in future research.

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Andreia Nogueira Pizarro, Jasper Schipperijn, José Carlos Ribeiro, António Figueiredo, Jorge Mota and Maria Paula Santos

Background:

Identifying where children spend their activity-time may help define relevant domains for effective PA promotion and better understand the relation between PA and environment. Our study aimed to identify how boys and girls allocate their active time in the different domains.

Methods:

374 children (201 girls; mean age = 11.7 years) wore an accelerometer and a GPS for 7 days. PALMS software combined data, categorized nonsedentary time and bouts of moderate-to-vigorous physical activity (MVPA). Geographical information system allocated activity into 4 domains: school, leisure, transport and home.

Results:

Overall, a higher proportion of time in MVPA was found in the transport domain (45.5%), school (30.5%), leisure (21.3%), and home (2.7%). Gender differences were found for the proportion of time spent across domains. Girls (54.5%) had more MVPA than boys (35.2%) in the transport domain, whereas boys spent more MVPA time in school (37.0%) and leisure (24.9%) than girls (24.7% and 18.1, respectively).

Conclusions:

Interventions to increase transport behavior may be relevant for children’s MVPA. School is an important domain for boys PA, while for girls increasing the supportiveness of the school environment for PA should be a priority. Strategies should consider gender differences when targeting each domain.