. Consumer preference for this trackable and human-scaled measurement is reflected by the fact that most contemporary wearable technologies (ie, devices) offer a step-counting feature. 2 The 2018 Physical Activity Guidelines Advisory Committee Scientific Report also recently advocated for the benefits of
Search Results
Toward Harmonized Treadmill-Based Validation of Step-Counting Wearable Technologies: A Scoping Review
Christopher C. Moore, Aston K. McCullough, Elroy J. Aguiar, Scott W. Ducharme, and Catrine Tudor-Locke
New Considerations for Wearable Technology Data: Changes in Running Biomechanics During a Marathon
Christian A. Clermont, Lauren C. Benson, W. Brent Edwards, Blayne A. Hettinga, and Reed Ferber
patterns during prolonged running. 10 Therefore, the first purpose of this study was to quantify subject-specific alterations in running patterns, using wearable technology data, throughout a marathon race. The second purpose of this study was to determine if runners could be clustered into separate
A Mine of Information: Can Sports Analytics Provide Wisdom From Your Data?
Louis Passfield and James G. Hopker
This paper explores the notion that the availability and analysis of large data sets have the capacity to improve practice and change the nature of science in the sport and exercise setting. The increasing use of data and information technology in sport is giving rise to this change. Web sites hold large data repositories, and the development of wearable technology, mobile phone applications, and related instruments for monitoring physical activity, training, and competition provide large data sets of extensive and detailed measurements. Innovative approaches conceived to more fully exploit these large data sets could provide a basis for more objective evaluation of coaching strategies and new approaches to how science is conducted. An emerging discipline, sports analytics, could help overcome some of the challenges involved in obtaining knowledge and wisdom from these large data sets. Examples of where large data sets have been analyzed, to evaluate the career development of elite cyclists and to characterize and optimize the training load of well-trained runners, are discussed. Careful verification of large data sets is time consuming and imperative before useful conclusions can be drawn. Consequently, it is recommended that prospective studies be preferred over retrospective analyses of data. It is concluded that rigorous analysis of large data sets could enhance our knowledge in the sport and exercise sciences, inform competitive strategies, and allow innovative new research and findings.
Wearable Technology for Athletes: Information Overload and Pseudoscience?
Shona L Halson, Jonathan M. Peake, and John P. Sullivan
Monitoring Athlete Training Loads: Consensus Statement
Pitre C. Bourdon, Marco Cardinale, Andrew Murray, Paul Gastin, Michael Kellmann, Matthew C. Varley, Tim J. Gabbett, Aaron J. Coutts, Darren J. Burgess, Warren Gregson, and N. Timothy Cable
Monitoring the load placed on athletes in both training and competition has become a very hot topic in sport science. Both scientists and coaches routinely monitor training loads using multidisciplinary approaches, and the pursuit of the best methodologies to capture and interpret data has produced an exponential increase in empirical and applied research. Indeed, the field has developed with such speed in recent years that it has given rise to industries aimed at developing new and novel paradigms to allow us to precisely quantify the internal and external loads placed on athletes and to help protect them from injury and ill health. In February 2016, a conference on “Monitoring Athlete Training Loads—The Hows and the Whys” was convened in Doha, Qatar, which brought together experts from around the world to share their applied research and contemporary practices in this rapidly growing field and also to investigate where it may branch to in the future. This consensus statement brings together the key findings and recommendations from this conference in a shared conceptual framework for use by coaches, sport-science and -medicine staff, and other related professionals who have an interest in monitoring athlete training loads and serves to provide an outline on what athlete-load monitoring is and how it is being applied in research and practice, why load monitoring is important and what the underlying rationale and prospective goals of monitoring are, and where athlete-load monitoring is heading in the future.
Toward Comprehensive Step-Based Physical Activity Guidelines: Are We Ready?
Catrine Tudor-Locke and Elroy J. Aguiar
in physical activity research, and step-based physical activity goals are increasingly popularized, for example, 10,000 steps/day ( Bassett, Toth, LaMunion, & Crouter, 2017 ). The growth and adoption of wearable technologies (including research-grade accelerometers, consumer-grade wearable devices
Wearable Device Validity in Determining Step Count During Hiking and Trail Running
James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning, and Mark DeBeliso
, Sattar, & Lean, 2017 ). In order for individuals to truly attain their step goals, the ability to accurately determine step count becomes important. Wearable technology was rated as the top fitness trend the past two years ( Thompson, 2015 , 2016 ), and this tendency is expected to grow as the use of
Wearable Activity Trackers in Clinical Research and Practice
David R. Bassett, Patty S. Freedson, and Dinesh John
( International Data Corp., 2017 ). The growth in the number of research publications about Fitbit is increasing exponentially (Figure 1 ). The global wearable-technology market, including activity trackers, is projected to grow from over $30 billion in 2016 to over $150 billion in 2026 ( CISION PR Newswire
On-Ice Physical Demands of World-Class Women’s Ice Hockey: From Training to Competition
Adam Douglas, Michael A. Rotondi, Joseph Baker, Veronica K. Jamnik, and Alison K. Macpherson
shown to be a valid and reliable measure to count sport-based explosive actions in female athletes. 16 , 17 With the increased use of wearable technology to measure the work being performed in other sports, there is no research applying this technology in the sport of ice hockey. The purpose of this
Global Positioning System Watches and Electronic Journals: Are Training-Load Measures Similar in High School Cross-Country Runners?
Micah C. Garcia and David M. Bazett-Jones
by a global positioning system [GPS] device) on average, running distance could be underestimated or overestimated by −28% to +40%. 15 Wearable technology allows for objective measurement of running duration and distance using GPS enabled devices (eg, watches, smartphones). GPS watches were on
