Published on in Vol 5, No 2 (2017): February

Accuracy and Adoption of Wearable Technology Used by Active Citizens: A Marathon Event Field Study

Accuracy and Adoption of Wearable Technology Used by Active Citizens: A Marathon Event Field Study

Accuracy and Adoption of Wearable Technology Used by Active Citizens: A Marathon Event Field Study

Journals

  1. Clermont C, Duffett-Leger L, Hettinga B, Ferber R. Runners’ Perspectives on ‘Smart’ Wearable Technology and Its Use for Preventing Injury. International Journal of Human–Computer Interaction 2020;36(1):31 View
  2. Janssen M, Walravens R, Thibaut E, Scheerder J, Brombacher A, Vos S. Understanding Different Types of Recreational Runners and How They Use Running-Related Technology. International Journal of Environmental Research and Public Health 2020;17(7):2276 View
  3. Strotbaum V, Pobiruchin M, Schreiweis B, Wiesner M, Strahwald B. Your data is gold – Data donation for better healthcare?. it - Information Technology 2019;61(5-6):219 View
  4. Gilgen-Ammann R, Schweizer T, Wyss T. Accuracy of Distance Recordings in Eight Positioning-Enabled Sport Watches: Instrument Validation Study. JMIR mHealth and uHealth 2020;8(6):e17118 View
  5. Stuckenschneider T, Askew C, Rüdiger S, Polidori M, Abeln V, Vogt T, Krome A, Olde Rikkert M, Lawlor B, Schneider S, Matura S. Cardiorespiratory Fitness and Cognitive Function are Positively Related Among Participants with Mild and Subjective Cognitive Impairment. Journal of Alzheimer's Disease 2018;62(4):1865 View
  6. Chacko S, Quinzi F, De Fano A, Bianco V, Mussini E, Berchicci M, Perri R, Di Russo F. A single bout of vigorous-intensity aerobic exercise affects reactive, but not proactive cognitive brain functions. International Journal of Psychophysiology 2020;147:233 View
  7. Morris J, Jones M, Thompson N, Wallace T, DeRuyter F. Clinician Perspectives on mRehab Interventions and Technologies for People with Disabilities in the United States: A National Survey. International Journal of Environmental Research and Public Health 2019;16(21):4220 View
  8. Doherty C, Keogh A, Davenport J, Lawlor A, Smyth B, Caulfield B. An evaluation of the training determinants of marathon performance: A meta-analysis with meta-regression. Journal of Science and Medicine in Sport 2020;23(2):182 View
  9. Fokkema T, van Damme A, Fornerod M, de Vos R, Bierma‐Zeinstra S, van Middelkoop M. Training for a (half‐)marathon: Training volume and longest endurance run related to performance and running injuries. Scandinavian Journal of Medicine & Science in Sports 2020;30(9):1692 View
  10. Benson L, Clermont C, Osis S, Kobsar D, Ferber R. Classifying running speed conditions using a single wearable sensor: Optimal segmentation and feature extraction methods. Journal of Biomechanics 2018;71:94 View
  11. Rüdiger S, Stuckenschneider T, Abeln V, Askew C, Wollseiffen P, Schneider S. Validation of a widely used heart rate monitor to track steps in older adults. The Journal of Sports Medicine and Physical Fitness 2019;59(10) View
  12. LaPlaca D, Turner H. Health Ramifications of Smart Devices. Strength & Conditioning Journal 2020;42(3):106 View
  13. Sollanek K, Liu M, Carballo A, Caldwell A, Cheuvront S. The accurate prediction of sweat rate from energy expenditure and air temperature: a proof-of-concept study. Applied Physiology, Nutrition, and Metabolism 2020;45(11):1299 View
  14. Kebede M, Steenbock B, Helmer S, Sill J, Möllers T, Pischke C. Identifying Evidence-Informed Physical Activity Apps: Content Analysis. JMIR mHealth and uHealth 2018;6(12):e10314 View
  15. Wiesner M, Zowalla R, Suleder J, Westers M, Pobiruchin M. Technology Adoption, Motivational Aspects, and Privacy Concerns of Wearables in the German Running Community: Field Study. JMIR mHealth and uHealth 2018;6(12):e201 View
  16. Silva A, Simões P, Queirós A, Rodrigues M, Rocha N. Mobile Apps to Quantify Aspects of Physical Activity: a Systematic Review on its Reliability and Validity. Journal of Medical Systems 2020;44(2) View
  17. Stragier J, Vanden Abeele M, De Marez L. Recreational athletes’ running motivations as predictors of their use of online fitness community features. Behaviour & Information Technology 2018;37(8):815 View
  18. Sanchis-Gomar F, Lavie C, Perez M. Consumer wearable technologies to identify and monitor exercise-related arrhythmias in athletes. Current Opinion in Cardiology 2021;36(1):10 View
  19. Lluch J, Rebollo M, Calduch-Losa A, Molla R. Precision of Wearable GPS in Marathon Races. IEEE Consumer Electronics Magazine 2021;10(1):32 View
  20. Chandrasekaran R, Katthula V, Moustakas E. Patterns of Use and Key Predictors for the Use of Wearable Health Care Devices by US Adults: Insights from a National Survey. Journal of Medical Internet Research 2020;22(10):e22443 View
  21. Singh P, Esposito M, Barrons Z, Clermont C, Wannop J, Stefanyshyn D. Measuring Gait Velocity and Stride Length with an Ultrawide Bandwidth Local Positioning System and an Inertial Measurement Unit. Sensors 2021;21(9):2896 View
  22. Adamakis M. Criterion Validity of iOS and Android Applications to Measure Steps and Distance in Adults. Technologies 2021;9(3):55 View
  23. Helsen K, Janssen M, Vos S, Scheerder J. Two of a Kind? Similarities and Differences between Runners and Walkers in Sociodemographic Characteristics, Sports Related Characteristics and Wearable Usage. International Journal of Environmental Research and Public Health 2022;19(15):9284 View
  24. Toresdahl B, Metzl J, Kinderknecht J, McElheny K, de Mille P, Quijano B, Fontana M. Training patterns associated with injury in New York City Marathon runners. British Journal of Sports Medicine 2023;57(3):146 View
  25. Alduaij M. Towards a Wearable Technology Model. International Journal of Information Systems in the Service Sector 2022;14(1):1 View
  26. Bube B, Zanón B, Lara Palma A, Klocke H. Wearable Devices in Diving: Scoping Review. JMIR mHealth and uHealth 2022;10(9):e35727 View
  27. Chan Z, Peeters R, Cheing G, Ferber R, Cheung R. Evaluation of COVID-19 Restrictions on Distance Runners' Training Habits Using Wearable Trackers. Frontiers in Sports and Active Living 2022;3 View
  28. Lacey A, Whyte E, O’Keeffe S, O’Connor S, Moran K, Mourot L. A qualitative examination of the factors affecting the adoption of injury focused wearable technologies in recreational runners. PLOS ONE 2022;17(7):e0265475 View
  29. Mayne R, Bleakley C, Matthews M. Use of monitoring technology and injury incidence among recreational runners: a cross-sectional study. BMC Sports Science, Medicine and Rehabilitation 2021;13(1) View
  30. Singh N, Misra R, Singh S, Rana N, Khorana S. Assessing the factors that influence the adoption of healthcare wearables by the older population using an extended PMT model. Technology in Society 2022;71:102126 View
  31. Pal D, Funilkul S, Papasratorn B. Antecedents of Trust and the Continuance Intention in IoT-Based Smart Products: The Case of Consumer Wearables. IEEE Access 2019;7:184160 View
  32. Byun H, Chiu W, Won D. The Voice from Users of Running Applications: An Analysis of Online Reviews Using Leximancer. Journal of Theoretical and Applied Electronic Commerce Research 2023;18(1):173 View
  33. Alexander J, Sovakova M, Rena G. Factors affecting resting heart rate in free-living healthy humans. DIGITAL HEALTH 2022;8:205520762211290 View
  34. Cloosterman K, Fokkema T, de Vos R, van Oeveren B, Bierma-Zeinstra S, van Middelkoop M. Feasibility and usability of GPS data in exploring associations between training load and running-related knee injuries in recreational runners. BMC Sports Science, Medicine and Rehabilitation 2022;14(1) View
  35. Vorlíček M, Stewart T, Schipperijn J, Burian J, Rubín L, Dygrýn J, Mitáš J, Duncan S. Smart Watch Versus Classic Receivers: Static Validity of Three GPS Devices in Different Types of Built Environments. Sensors 2021;21(21):7232 View
  36. Pal D, Vanijja V, Arpnikanondt C, Zhang X, Papasratorn B. A Quantitative Approach for Evaluating the Quality of Experience of Smart-Wearables From the Quality of Data and Quality of Information: An End User Perspective. IEEE Access 2019;7:64266 View
  37. Benson L, Räisänen A, Clermont C, Ferber R. Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis. Sensors 2022;22(5):1722 View
  38. Mertala P, Palsa L. Running free: recreational runners’ reasons for non-use of digital sports technology. Sport in Society 2024;27(3):329 View
  39. Palsa L, Mertala P. Contextualizing Everyday Data Literacies: The Case of Recreational Runners. International Journal of Human–Computer Interaction 2023:1 View
  40. Volkova V, Ferber R, Pasanen K, Kenny S. Perceptions and Attitudes Toward the Use of Wearable Technology in the Dance Studio Environment. Journal of Dance Medicine & Science 2023;27(4):241 View
  41. Kiernan D, Katzman Z, Hawkins D, Christiansen B. A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running. Sensors 2024;24(2):656 View
  42. Van Hooren B, Plasqui G, Meijer K. The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial. The American Journal of Sports Medicine 2024;52(3):750 View
  43. Mikoś M, Kazmierski K, Wachulec N, Sośnica K. Accuracy of satellite positioning using GNSS receivers in sports watches. Measurement 2024;229:114426 View
  44. Thomas M, Boursalie O, Samavi R, Doyle T. Data-driven approach to quantify trust in medical devices using Bayesian networks. Experimental Biology and Medicine 2023;248(24):2578 View
  45. Chowdhary K, Crockett Z, Chua J, Soo Hoo J. Exploring the Relationship between Running-Related Technology Use and Running-Related Injuries: A Cross-Sectional Study of Recreational and Elite Long-Distance Runners. Healthcare 2024;12(6):642 View
  46. Tóth K, Takács P, Balatoni I. Users’ Expectations of Smart Devices during Physical Activity—A Literature Review. Applied Sciences 2024;14(8):3518 View

Books/Policy Documents

  1. Thomas M, Boursalie O, Samavi R, Doyle T. Artificial Intelligence for Personalized Medicine. View