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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Runners’ Perspectives on ‘Smart’ Wearable Technology and Its Use for Preventing Injury
Christian A. Clermont, Linda Duffett‐Leger, Blayne A. Hettinga, et al.
International Journal of Human-Computer Interaction (2019) Vol. 36, Iss. 1, pp. 31-40
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis
Lauren C. Benson, Anu M. Räisänen, Christian A. Clermont, et al.
Sensors (2022) Vol. 22, Iss. 5, pp. 1722-1722
Open Access | Times Cited: 68
E-Textiles for Sports and Fitness Sensing: Current State, Challenges, and Future Opportunities
Kai Yang, Stuart A. McErlain‐Naylor, Beckie Isaia, et al.
Sensors (2024) Vol. 24, Iss. 4, pp. 1058-1058
Open Access | Times Cited: 15
Real-time feedback by wearables in running: Current approaches, challenges and suggestions for improvements
Bas Van Hooren, Jos Goudsmit, Juan Restrepo, et al.
Journal of Sports Sciences (2019) Vol. 38, Iss. 2, pp. 214-230
Open Access | Times Cited: 100
Understanding Different Types of Recreational Runners and How They Use Running-Related Technology
Mark Janssen, Ruben Walravens, Erik Thibaut, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 7, pp. 2276-2276
Open Access | Times Cited: 87
Wearables for Running Gait Analysis: A Systematic Review
Rachel Mason, Liam T. Pearson, Gill Barry, et al.
Sports Medicine (2022) Vol. 53, Iss. 1, pp. 241-268
Open Access | Times Cited: 65
The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial
Bas Van Hooren, Guy Plasqui, Kenneth Meijer
The American Journal of Sports Medicine (2024) Vol. 52, Iss. 3, pp. 750-765
Open Access | Times Cited: 8
Predicting Sports Injuries with Wearable Technology and Data Analysis
Amir Hassan Zadeh, David Taylor, Margaret Bertsos, et al.
Information Systems Frontiers (2020) Vol. 23, Iss. 4, pp. 1023-1037
Closed Access | Times Cited: 60
The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review
Ezio Preatoni, Elena Bergamini, Silvia Fantozzi, et al.
Sensors (2022) Vol. 22, Iss. 9, pp. 3225-3225
Open Access | Times Cited: 36
Exploring the Rise of Smart Wearables: A Bibliometric Analysis on the Growing Use of Fitness Applications Among Athletes
Charu Saxena, M. A. F. Singh
Kinesiology Review (2025), pp. 1-14
Closed Access
A Task-Technology-Identity Fit Model of Smartwatch Utilisation and User Satisfaction: A Hybrid SEM-Neural Network Approach
Mazen El-Masri, Karim Al‐Yafi, Muhammad Mustafa Kamal
Information Systems Frontiers (2022)
Open Access | Times Cited: 19
How Are Sports-Trackers Used by Runners? Running-Related Data, Personal Goals, and Self-Tracking in Running
Armağan Karahanoğlu, Rúben Gouveia, Jasper Reenalda, et al.
Sensors (2021) Vol. 21, Iss. 11, pp. 3687-3687
Open Access | Times Cited: 26
Downhill running increases markers of muscle damage and impairs the maximal voluntary force production as well as the late phase of the rate of voluntary force development
Giuseppe Coratella, Giorgio Varesco, Vianney Rozand, et al.
European Journal of Applied Physiology (2024) Vol. 124, Iss. 6, pp. 1875-1883
Open Access | Times Cited: 3
Influence of Extrinsic and Intrinsic Attributes on Consumers’ Attitude and Intention of Using Wearable Technology
Sonia Bakhshian, Young‐A Lee
International Journal of Human-Computer Interaction (2022) Vol. 39, Iss. 3, pp. 562-574
Closed Access | Times Cited: 14
Runner’s Perceptions of Reasons to Quit Running: Influence of Gender, Age and Running-Related Characteristics
Daphne Menheere, Mark Janssen, Mathias Funk, et al.
International Journal of Environmental Research and Public Health (2020) Vol. 17, Iss. 17, pp. 6046-6046
Open Access | Times Cited: 22
Contextualizing Everyday Data Literacies: The Case of Recreational Runners
Lauri Palsa, Pekka Mertala
International Journal of Human-Computer Interaction (2023) Vol. 40, Iss. 19, pp. 5845-5856
Open Access | Times Cited: 7
Identifying key quality features for wearable technology embedded products using the Kano model
Mir Salahuddin, Young‐A Lee
International Journal of Clothing Science and Technology (2020) Vol. 33, Iss. 1, pp. 93-105
Closed Access | Times Cited: 18
Running free: recreational runners’ reasons for non-use of digital sports technology
Pekka Mertala, Lauri Palsa
Sport in Society (2023) Vol. 27, Iss. 3, pp. 329-345
Open Access | Times Cited: 6
Revolutionizing Sport - How Technology is Changing the Sports Industry?
Pelin Avcı, Akan Bayrakdar
Özgür Yayınları eBooks (2023)
Open Access | Times Cited: 5
Estimating Knee Movement Patterns of Recreational Runners Across Training Sessions Using Multilevel Functional Regression Models
Marcos Matabuena, Marta Karas, Sherveen Riazati, et al.
The American Statistician (2022) Vol. 77, Iss. 2, pp. 169-181
Open Access | Times Cited: 8
A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running
Dovin Kiernan, Zachary David Katzman, David Hawkins, et al.
Sensors (2024) Vol. 24, Iss. 2, pp. 656-656
Open Access | Times Cited: 1
Measuring Gait Velocity and Stride Length with an Ultrawide Bandwidth Local Positioning System and an Inertial Measurement Unit
Pratham Singh, Michael Esposito, Zach B. Barrons, et al.
Sensors (2021) Vol. 21, Iss. 9, pp. 2896-2896
Open Access | Times Cited: 11
How Do Runners Experience Personalization of Their Training Scheme: The Inspirun E-Coach?
Mark Janssen, Jos Goudsmit, Coen Lauwerijssen, et al.
Sensors (2020) Vol. 20, Iss. 16, pp. 4590-4590
Open Access | Times Cited: 11
How Precisely Can Easily Accessible Variables Predict Achilles and Patellar Tendon Forces during Running?
René Børge Korsgaard Brund, Rasmus Waagepetersen, Rasmus Oestergaard Nielsen, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7418-7418
Open Access | Times Cited: 10
A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology
Joshua Autton Carter, Adrian Rodriguez Rivadulla, Ezio Preatoni
Sports Biomechanics (2022), pp. 1-18
Open Access | Times Cited: 7
Internet of Intelligent Things: Injection of Intelligence into IoT Devices
Simar Preet Singh, Arun Solanki, Tarana Singh, et al.
Elsevier eBooks (2021), pp. 85-102
Closed Access | Times Cited: 9
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