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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:

Subject-specific and group-based running pattern classification using a single wearable sensor
Nizam Uddin Ahamed, Dylan Kobsar, Lauren C. Benson, et al.
Journal of Biomechanics (2019) Vol. 84, pp. 227-233
Closed Access | Times Cited: 41

Showing 1-25 of 41 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: 70
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: 67
Flexible, stretchable, breathable and sweatproof all-nanofiber iontronic tactile sensor for continuous and comfortable knee joint motion monitoring
Peng Wang, Jun Liu, Wei Yu, et al.
Nano Energy (2022) Vol. 103, pp. 107768-107768
Closed Access | Times Cited: 50
Automated Accelerometer-Based Gait Event Detection During Multiple Running Conditions
Lauren C. Benson, Christian A. Clermont, Ricky Watari, et al.
Sensors (2019) Vol. 19, Iss. 7, pp. 1483-1483
Open Access | Times Cited: 57
A hierarchical cluster analysis to determine whether injured runners exhibit similar kinematic gait patterns
Susanne Jauhiainen, Andrew J. Pohl, Sami Äyrämö, et al.
Scandinavian Journal of Medicine and Science in Sports (2020) Vol. 30, Iss. 4, pp. 732-740
Closed Access | Times Cited: 51
Workload a-WEAR-ness: Monitoring Workload in Team Sports With Wearable Technology. A Scoping Review
Lauren C. Benson, Anu M. Räisänen, Valeriya G. Volkova, et al.
Journal of Orthopaedic and Sports Physical Therapy (2020) Vol. 50, Iss. 10, pp. 549-563
Closed Access | Times Cited: 41
Recent Machine Learning Progress in Lower Limb Running Biomechanics With Wearable Technology: A Systematic Review
Liangliang Xiang, Alan Wang, Yaodong Gu, et al.
Frontiers in Neurorobotics (2022) Vol. 16
Open Access | Times Cited: 25
Tibial Acceleration-Based Prediction of Maximal Vertical Loading Rate During Overground Running: A Machine Learning Approach
Rud Derie, Pieter Robberechts, Pieter Van den Berghe, et al.
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 30
Foot type classification using sensor-enabled footwear and 1D-CNN
Zhanyong Mei, Kamen Ivanov, Guoru Zhao, et al.
Measurement (2020) Vol. 165, pp. 108184-108184
Open Access | Times Cited: 29
New Considerations for Collecting Biomechanical Data Using Wearable Sensors: The Effect of Different Running Environments
Lauren C. Benson, Christian A. Clermont, Reed Ferber
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 27
Subject-specific sensitivity of several biomechanical features to fatigue during an exhaustive treadmill run
Christos Chalitsios, Thomas Nikodelis, Georgios Mavrommatis, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Foot Pronation Prediction with Inertial Sensors during Running: A Preliminary Application of Data-Driven Approaches
Liangliang Xiang, Yaodong Gu, Alan Wang, et al.
Journal of Human Kinetics (2023)
Open Access | Times Cited: 6
The Relationship between VO2max, Power Management, and Increased Running Speed: Towards Gait Pattern Recognition through Clustering Analysis
Juan Pardo, Melanie Mir-Jimenez, Vanessa Hueso Moreno, et al.
Sensors (2021) Vol. 21, Iss. 7, pp. 2422-2422
Open Access | Times Cited: 14
Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification
Tasriva Sikandar, Mohammad Fazle Rabbi, Kamarul Hawari Ghazali, et al.
Sensors (2021) Vol. 21, Iss. 8, pp. 2836-2836
Open Access | Times Cited: 13
K-mer-Based Human Gesture Recognition (KHGR) Using Curved Piezoelectric Sensor
Sathishkumar Subburaj, Chih-Ho Yeh, Brijesh Patel, et al.
Electronics (2023) Vol. 12, Iss. 1, pp. 210-210
Open Access | Times Cited: 5
Gait Classification with Gait Inherent Attribute Identification from Ankle’s Kinematics
Yogesh Singh, Vineet Vashista
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 30, pp. 833-842
Open Access | Times Cited: 8
Analyzing Optimal Wearable Motion Sensor Placement for Accurate Classification of Fall Directions
Sokea Teng, Jung-Yeon Kim, Seob Jeon, et al.
Sensors (2024) Vol. 24, Iss. 19, pp. 6432-6432
Open Access | Times Cited: 1
New Considerations for Collecting Biomechanical Data Using Wearable Sensors: How Does Inclination Influence the Number of Runs Needed to Determine a Stable Running Gait Pattern?
Nizam Uddin Ahamed, Lauren C. Benson, Christian A. Clermont, et al.
Sensors (2019) Vol. 19, Iss. 11, pp. 2516-2516
Open Access | Times Cited: 13
Using Machine Learning and Wearable Inertial Sensor Data for the Classification of Fractal Gait Patterns in Women and Men During Load Carriage
Nizam Uddin Ahamed, Kellen T. Krajewski, Camille C. Johnson, et al.
Procedia Computer Science (2021) Vol. 185, pp. 282-291
Open Access | Times Cited: 10
Study on foot-type classification for young adults based on static and dynamic plantar pressure distribution
Xinyao Tang, Xupeng Wang, Xiaomin Ji, et al.
Advances in Mechanical Engineering (2022) Vol. 14, Iss. 5
Open Access | Times Cited: 6
Evaluating the difference in walk patterns among normal-weight and overweight/obese individuals in real-world surfaces using statistical analysis and deep learning methods with inertial measurement unit data
Tasriva Sikandar, Mohammad Fazle Rabbi, Kamarul Hawari Ghazali, et al.
Physical and Engineering Sciences in Medicine (2022) Vol. 45, Iss. 4, pp. 1289-1300
Closed Access | Times Cited: 6
Minimum number of inertial measurement units needed to identify significant variations in walk patterns of overweight individuals walking on irregular surfaces
Tasriva Sikandar, Mohammad Fazle Rabbi, Kamarul Hawari Ghazali, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 3
Seamless Temporal Gait Evaluation during Walking and Running Using Two IMU Sensors
Yonatan Hutabarat, Dai Owaki, Mitsuhiro Hayashibe
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2021), pp. 6835-6840
Closed Access | Times Cited: 5
Ensemble-Based Machine Learning Algorithms for Classifying Breast Tissue Based on Electrical Impedance Spectroscopy
Sam Matiur Rahman, Md. Asraf Ali, Omar Altwijri, et al.
Advances in intelligent systems and computing (2019), pp. 260-266
Closed Access | Times Cited: 4
Mapping-Based Dosage of Gait Modification Selection for Multi-Parameter, Subject-Specific Gait Retraining
Junkai Xu, Fangyuan Cao, Shi Zhan, et al.
IEEE Access (2020) Vol. 8, pp. 106354-106363
Open Access | Times Cited: 4
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