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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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Wayne Brown and Matt Greig

The epidemiology and etiology of ankle sprain injuries in soccer have been well described. Retrospective analysis of epidemiological data identified an English Premier League player sustaining a high lateral ankle sprain. GPS data collated during the training session in which the injury was sustained, and subsequent rehabilitation sessions, were analyzed to quantify uniaxial PlayerLoad metrics. The injured player revealed a 3:1 asymmetrical loading pattern in the mediolateral plane and multiaxial high loading events which might present the inciting event to injury. The high magnitude, asymmetrical and multiplanar loading is consistent with lateral ankle sprain etiology.

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Josh L. Secomb, Jeremy M. Sheppard and Ben J. Dascombe

Purpose:

To provide a descriptive and quantitative time–motion analysis of surfing training with the use of global positioning system (GPS) and heart-rate (HR) technology.

Methods:

Fifteen male surfing athletes (22.1 ± 3.9 y, 175.4 ± 6.4 cm, 72.5 ± 7.7 kg) performed a 2-h surfing training session, wearing both a GPS unit and an HR monitor. An individual digital video recording was taken of the entire surfing duration. Repeated-measures ANOVAs were used to determine any effects of time on the physical and physiological measures.

Results:

Participants covered 6293.2 ± 1826.1 m during the 2-h surfing training session and recorded measures of average speed, HRaverage, and HRpeak as 52.4 ± 15.2 m/min, 128 ± 13 beats/min, and 171 ± 12 beats/min, respectively. Furthermore, the relative mean times spent performing paddling, sprint paddling to catch waves, stationary, wave riding, and recovery of the surfboard were 42.6% ± 9.9%, 4.1% ± 1.2%, 52.8% ± 12.4%, 2.5% ± 1.9%, and 2.1% ± 1.7%, respectively.

Conclusion:

The results demonstrate that a 2-h surfing training session is performed at a lower intensity than competitive heats. This is likely due to the onset of fatigue and a pacing strategy used by participants. Furthermore, surfing training sessions do not appear to appropriately condition surfers for competitive events. As a result, coaches working with surfing athletes should consider altering training sessions to incorporate repeated-effort sprint paddling to more effectively physically prepare surfers for competitive events.

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Gregory Roe, Joshua Darrall-Jones, Christopher Black, William Shaw, Kevin Till and Ben Jones

Purpose:

The purpose of this study was to investigate the validity of timing gates and 10-Hz global positioning systems (GPS) units (Catapult Optimeye S5) against a criterion measure (50-Hz radar gun) for assessing maximum sprint velocity (Vmax).

Methods:

Nine male professional rugby union players performed 3 maximal 40-m sprints with 3 min rest between efforts with Vmax assessed simultaneously via timing gates, 10-Hz GPSOpen (Openfield software), GPSSprint (Sprint software), and radar gun. Eight players wore 3 GPS units, while 1 wore a single unit during each sprint.

Results:

When compared with the radar gun, mean biases for GPSOpen, GPSSprint, and timing gates were trivial, small, and small, respectively. The typical error of the estimate (TEE) was small for timing gate and GPSOpen while moderate for GPSSprint. Correlations with radar gun were nearly perfect for all measures. Mean bias, TEE, and correlations between GPS units were trivial, small, and nearly perfect, respectively, while a small TEE existed when GPSOpenfield was compared with GPSSprint.

Conclusion:

Based on these findings, both 10-Hz GPS and timing gates provide valid measures of 40-m Vmax assessment compared with a radar gun. However, as error did exist between measures, the same testing protocol should be used when assessing 40-m Vmax over time. Furthermore, in light of the above results, it is recommended that when assessing changes in GPS-derived Vmax over time, practitioners should use the same unit for each player and perform the analysis with the same software, preferably Catapult Openfield.

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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.

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Carl Petersen, David B. Pyne, Marc R. Portus, Stuart Karppinen and Brian Dawson

Purpose:

The time-motion characteristics and the within-athlete variability in movement patterns were quantified for the same male fast bowler playing One Day International (ODI) cricket matches (n = 12).

Methods:

A number of different time motion characteristics were monitored using a portable 5-Hz global positioning system (GPS) unit (Catapult, Melbourne, Australia).

Results:

The bowler’s mean workload per ODI was 8 ± 2 overs (mean ± SD). He covered a total distance of 15.9 ± 2.5 km per game; 12 ± 3% or 1.9 ± 0.2 km was striding (0.8 ± 0.2 km) or sprinting (1.1 ± 0.2 km), whereas 10.9 ± 2.1 km was spent walking. One high-intensity (running, striding, or sprinting) repetition (HIR) occurred every 68 ± 12 s, and the average duration of a HI effort was 2.7 ± 0.1 s. The player also completed 66 ± 11 sprints per game; mean sprint distance was 18 ± 3 m and maximum sprinting speed 8.3 ± 0.9 m·s−1.

Conclusions:

The movement patterns of this fast bowler were a combination of highly intermittent activities of variable intensity on the base of ~16 km per game. This information provides insight for conditioning coaches to determine the physical demands and to adapt the training and recovery processes of ODI fast bowlers.

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Will Vickery, Ben Dascombe and Rob Duffield

Purpose:

To examine the relationship between session rating of perceived exertion (sRPE) and measures of internal and external training load (TL) in cricket batsmen and medium-fast bowlers during net-based training sessions.

Methods:

The internal (heart rate), external (movement demands, PlayerLoad), and technical (cricket-specific skills) loads of 30 male cricket players (age 21.2 ± 3.8 y, height 1.82 ± 0.07 m, body mass 79.0 ± 8.7 kg) were determined from net-based cricket-training sessions (n = 118). The relationships between sRPE and measures of TL were quantified using Pearson product–moment correlations respective to playing position. Stepwise multiple-regression techniques provided key internal- and external-load determinants of sRPE in cricket players.

Results:

Significant correlations were evident (r = -.34 to .87, P < .05) between internal and external measures of TL and sRPE, with the strongest correlations (r ≥ .62) for GPS-derived measures for both playing positions. In batsmen, stepwise multiple-regression analysis revealed that 67.8% of the adjusted variance in sRPE could be explained by PlayerLoad and high-intensity distance (y = 27.43 + 0.81 PlayerLoad + 0.29 high-intensity distance). For medium-fast bowlers, 76.3% of the adjusted variance could be explained by total distance and mean heart rate (y = 101.82 + total distance 0.05 + HRmean – 0.48).

Conclusion:

These results suggest that sRPE is a valid method of reporting TL among cricket batsmen and medium-fast bowlers. Position-specific responses are evident and should be considered when monitoring the TL of cricket players.

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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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Luis Suarez-Arrones, Carlos Arenas, Guillermo López, Bernardo Requena, Oliver Terrill and Alberto Mendez-Villanueva

Purpose:

This study describes the physical match demands relative to positional group in male rugby sevens.

Methods:

Ten highly trained players were investigated during competitive matches (N = 23) using GPS technology, heart rate (HR), and video recording.

Results:

The relative distance covered by the players throughout the match was 102.3 ± 9.8 m/min. As a percentage of total distance, 35.8% (36.6 ± 5.9 m/min) was covered walking, 26.0% (26.6 ± 5.5 m/min) jogging, 10.0% (10.2 ± 2.4 m/min) running at low intensity, 14.2% (14.5 ± 4.0 m/min) at medium intensity, 4.6% (4.7 ± 1.6 m/min) at high intensity, and 9.5% (9.7 ± 3.7 m/min) sprinting. For the backs, a substantial decrease in total distance and distance covered at low, medium, and high intensity was observed in the second half. Forwards exhibited a substantial decrease in the distance covered at medium intensity, high intensity, and sprinting in the 2nd half. Backs covered substantially more total distance at medium and sprinting speeds than forwards. In addition, the maximum length of sprint runs was substantially greater for the backs than forwards. On the contrary, forwards performed more tackles. The mean HR during the match in backs and forwards was similar, with the exception of time spent at HR intensities >90%HRmax, which was substantially higher in forwards.

Conclusion:

These findings provide a description of the different physical demands placed on rugby sevens backs and forwards. This information may be helpful in the development of positional and/or individualized physical-fitness training programs.