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
Levi Frehlich, Christine Friedenreich, Alberto Nettel-Aguirre, Jasper Schipperijn and Gavin R. McCormack
James J. Malone, Ric Lovell, Matthew C. Varley and Aaron J. Coutts
Athlete-tracking devices that include global positioning system (GPS) and microelectrical mechanical system (MEMS) components are now commonplace in sport research and practice. These devices provide large amounts of data that are used to inform decision making on athlete training and performance. However, the data obtained from these devices are often provided without clear explanation of how these metrics are obtained. At present, there is no clear consensus regarding how these data should be handled and reported in a sport context. Therefore, the aim of this review was to examine the factors that affect the data produced by these athlete-tracking devices and to provide guidelines for collecting, processing, and reporting of data. Many factors including device sampling rate, positioning and fitting of devices, satellite signal, and data-filtering methods can affect the measures obtained from GPS and MEMS devices. Therefore researchers are encouraged to report device brand/model, sampling frequency, number of satellites, horizontal dilution of precision, and software/firmware versions in any published research. In addition, details of inclusion/exclusion criteria for data obtained from these devices are also recommended. Considerations for the application of speed zones to evaluate the magnitude and distribution of different locomotor activities recorded by GPS are also presented, alongside recommendations for both industry practice and future research directions. Through a standard approach to data collection and procedure reporting, researchers and practitioners will be able to make more confident comparisons from their data, which will improve the understanding and impact these devices can have on athlete performance.
Helen J. Moore, Catherine A. Nixon, Amelia A. Lake, Wayne Douthwaite, Claire L. O’Malley, Claire L. Pedley, Carolyn D. Summerbell and Ashley C. Routen
Evidence suggests that many contemporary urban environments do not support healthy lifestyle choices and are implicated in the obesity pandemic. Middlesbrough, in the northeast of England is one such environment and a prime target for investigation.
To measure physical activity (PA) levels in a sample of 28 adolescents (aged 11 to 14 years) and describe the environmental context of their activity and explore where they are most and least active over a 7-day period, accelerometry and Global Positioning System (GPS) technology were used. Twenty-five of these participants also took part in focus groups about their experiences and perceptions of PA engagement.
Findings indicated that all participants were relatively inactive throughout the observed period although bouts of moderate-vigorous physical activity (MVPA) were identified in 4 contexts: school, home, street, and rural/urban green spaces, with MVPA levels highest in the school setting. Providing access to local facilities and services (such as leisure centers) is not in itself sufficient to engage adolescents in MVPA.
Factors influencing engagement in MVPA were identified within and across contexts, including ‘time’ as both a facilitator and barrier, perceptions of ‘gendered’ PA, and the social influences of peer groups and family members.
Marco Cardinale and Matthew C. Varley
The need to quantify aspects of training to improve training prescription has been the holy grail of sport scientists and coaches for many years. Recently, there has been an increase in scientific interest, possibly due to technological advancements and better equipment to quantify training activities. Over the last few years there has been an increase in the number of studies assessing training load in various athletic cohorts with a bias toward subjective reports and/or quantifications of external load. There is an evident lack of extensive longitudinal studies employing objective internal-load measurements, possibly due to the cost-effectiveness and invasiveness of measures necessary to quantify objective internal loads. Advances in technology might help in developing better wearable tools able to ease the difficulties and costs associated with conducting longitudinal observational studies in athletic cohorts and possibly provide better information on the biological implications of specific external-load patterns. Considering the recent technological developments for monitoring training load and the extensive use of various tools for research and applied work, the aim of this work was to review applications, challenges, and opportunities of various wearable technologies.
Avish P. Sharma, Philo U. Saunders, Laura A. Garvican-Lewis, Brad Clark, Jamie Stanley, Eileen Y. Robertson and Kevin G. Thompson
To determine the effect of training at 2100-m natural altitude on running speed (RS) during training sessions over a range of intensities relevant to middle-distance running performance.
In an observational study, 19 elite middle-distance runners (mean ± SD age 25 ± 5 y, VO2max, 71 ± 5 mL · kg–1 · min–1) completed either 4–6 wk of sea-level training (CON, n = 7) or a 4- to 5-wk natural altitude-training camp living at 2100 m and training at 1400–2700 m (ALT, n = 12) after a period of sea-level training. Each training session was recorded on a GPS watch, and athletes also provided a score for session rating of perceived exertion (sRPE). Training sessions were grouped according to duration and intensity. RS (km/h) and sRPE from matched training sessions completed at sea level and 2100 m were compared within ALT, with sessions completed at sea level in CON describing normal variation.
In ALT, RS was reduced at altitude compared with sea level, with the greatest decrements observed during threshold- and VO2max-intensity sessions (5.8% and 3.6%, respectively). Velocity of low-intensity and race-pace sessions completed at a lower altitude (1400 m) and/or with additional recovery was maintained in ALT, though at a significantly greater sRPE (P = .04 and .05, respectively). There was no change in velocity or sRPE at any intensity in CON.
RS in elite middle-distance athletes is adversely affected at 2100-m natural altitude, with levels of impairment dependent on the intensity of training. Maintenance of RS at certain intensities while training at altitude can result in a higher perceived exertion.
-supportive changes in their educational environments. To enable useful, standardized data collection, citizen scientists used a simple GPS-enabled mobile app capable of collecting geocoded visual and auditory data about walking routes and relevant environmental features. Results: The Our Voice framework is being
Yolanda Barrado-Martín, Michelle Heward, Remco Polman and Samuel R. Nyman
. , & Waldemar , G. ( 2014 ). Moderate-to-high intensity aerobic exercise in patients with mild to moderate Alzheimer’s disease: A pilot study . International Journal of Geriatric Psychiatry, 29 ( 12 ), 1242 – 1248 . PubMed ID: 24733599 doi:10.1002/gps.4096 10.1002/gps.4096 Gillespie , L
Nicolas Hobson, Sherry L. Dupuis, Lora M. Giangregorio and Laura E. Middleton
the United States . The Qualitative Report, 20 ( 12 ), 1960 – 1973 . Husband , J.H. ( 2000 ). Diagnostic disclosure in dementia: an opportunity for intervention? Geriatric Psychiatry, 15 ( 6 ), 544 – 547 . PubMed ID: 10861922 doi: 10.1002/1099-1166(200006)15:6<544::AID-GPS241>3.0.CO;2
Christina M. Patch, Caterina G. Roman, Terry L. Conway, Ralph B. Taylor, Kavita A. Gavand, Brian E. Saelens, Marc A. Adams, Kelli L. Cain, Jessa K. Engelberg, Lauren Mayes, Scott C. Roesch and James F. Sallis
neighborhood walkability and GPS-measured walking, bicycling and vehicle time in adolescents . Health Place . 2015 ; 32 : 1 – 7 . PubMed ID: 25588788 doi:10.1016/j.healthplace.2014.12.008 25588788 10.1016/j.healthplace.2014.12.008 62. Frank LD , Saelens BE , Chapman J , et al . Objective assessment