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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:

Predicting Knee Joint Kinematics from Wearable Sensor Data in People with Knee Osteoarthritis and Clinical Considerations for Future Machine Learning Models
Jay-Shian Tan, Sawitchaya Tippaya, Tara Binnie, et al.
Sensors (2022) Vol. 22, Iss. 2, pp. 446-446
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

Osteo-NeT: An Automated System for Predicting Knee Osteoarthritis from X-ray Images Using Transfer-Learning-Based Neural Networks Approach
Hassan A. Alshamrani, Mamoon Rashid, Sultan S. Alshamrani, et al.
Healthcare (2023) Vol. 11, Iss. 9, pp. 1206-1206
Open Access | Times Cited: 22
Validity and reliability of accelerations and orientations measured using wearable sensors during functional activities
Tomasz Cudejko, Kate Button, Mohammad Al-Amri
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 27
Prognostics of the knee osteoarthritis induced by cyclic loading activities. A model-based analysis
Fatima Zahra Mekrane, Radouane Ouladsine, Abdelwahed Barkaoui, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2025), pp. 1-14
Closed Access
Development of a Wearable Sleeve-Based System Combining Polymer Optical Fiber Sensors and an LSTM Network for Estimating Knee Kinematics
Benito Lorenzo Pugliese, Alessandra Angelucci, Federico Parisi, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2025) Vol. 33, pp. 728-738
Open Access
Development of a Microcontroller-Based Recurrent Neural Network Predictive System for Lower Limb Exoskeletons
T. Slucock, Gary N. Howells, Sanaul Hoque, et al.
Journal of Intelligent & Robotic Systems (2025) Vol. 111, Iss. 1
Open Access
Predicting Severe Knee Arthritis Based on Two Inertial Measurement Unit Sensors as a Dynamic Coordinate System Using Classical Machine Learning
Erfan Azizi, Mohammadsadegh Darbankhalesi, Amirhossein Zare, et al.
Journal of Medical Signals & Sensors (2025) Vol. 15, Iss. 3
Open Access
Hybrid Techniques of X-ray Analysis to Predict Knee Osteoarthritis Grades Based on Fusion Features of CNN and Handcrafted
Khalid Ahmed, Ebrahim Mohammed Senan, Khalil AL-Wagih, et al.
Diagnostics (2023) Vol. 13, Iss. 9, pp. 1609-1609
Open Access | Times Cited: 15
Technological Advancements and Elucidation Gadgets for Healthcare Applications: An Exhaustive Methodological Review-Part-I (AI, Big Data, Block Chain, Open-Source Technologies, and Cloud Computing)
Sridhar Siripurapu, Naresh K. Darimireddy, Abdellah Chehri, et al.
Electronics (2023) Vol. 12, Iss. 3, pp. 750-750
Open Access | Times Cited: 12
Inertial Sensors for Human Motion Analysis: A Comprehensive Review
Sara García-de-Villa, David Casillas-Pérez, Ana Jiménez-Martín, et al.
IEEE Transactions on Instrumentation and Measurement (2023) Vol. 72, pp. 1-39
Open Access | Times Cited: 11
The Influence of Gait Phase on Predicting Lower-Limb Joint Angles
David Hollinger, Mark C. Schall, Howard Chen, et al.
IEEE Transactions on Medical Robotics and Bionics (2023) Vol. 5, Iss. 2, pp. 343-352
Closed Access | Times Cited: 10
3D Knee and Hip Angle Estimation With Reduced Wearable IMUs via Transfer Learning During Yoga, Golf, Swimming, Badminton, and Dance
Jinxuan Li, Kezhe Zhu, Dongxuan Li, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 325-338
Open Access | Times Cited: 3
Deep Learning for Quantified Gait Analysis: A Systematic Literature Review
Adil Khan, Omar Galarraga, Sonia Garcia-Salicetti, et al.
IEEE Access (2024) Vol. 12, pp. 138932-138957
Open Access | Times Cited: 3
Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis
Giacomo Di Raimondo, Miel Willems, Bryce A. Killen, et al.
Sensors (2023) Vol. 23, Iss. 9, pp. 4484-4484
Open Access | Times Cited: 9
IJES-OA Net: A residual neural network to classify knee osteoarthritis from radiographic images based on the edges of the intra-joint spaces
Nacer Farajzadeh, Nima Sadeghzadeh, Mahdi Hashemzadeh
Medical Engineering & Physics (2023) Vol. 113, pp. 103957-103957
Closed Access | Times Cited: 8
Machine learning-based prediction of hip joint moment in healthy subjects, patients and post-operative subjects
Mattia Perrone, Steven P. Mell, John T. Martin, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2024), pp. 1-5
Open Access | Times Cited: 2
3D gait analysis in children using wearable sensors: feasibility of predicting joint kinematics and kinetics with personalized machine learning models and inertial measurement units
Shima Mohammadi Moghadam, Pablo Ortega Auriol, Ted Yeung, et al.
Frontiers in Bioengineering and Biotechnology (2024) Vol. 12
Open Access | Times Cited: 2
Precision Medicine–Based Machine Learning Analyses to Explore Optimal Exercise Therapies for Individuals With Knee Osteoarthritis: Random Forest-Informed Tree-Based Learning
Siyeon Kim, Michael R. Kosorok, Liubov Arbeeva, et al.
The Journal of Rheumatology (2023) Vol. 50, Iss. 10, pp. 1341-1345
Closed Access | Times Cited: 7
On the prediction of tibiofemoral contact forces for healthy individuals and osteoarthritis patients during gait: a comparative study of regression methods
Felipe Arruda Moura, Alexandre Roberto Marcondes Pelegrinelli, Danilo S. Catelli, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
A Kinematically-Informed Approach to Near Future Joint Angle Estimation at the Ankle
Ryan S. Pollard, David Hollinger, Iván Nail-Ulloa, et al.
IEEE Transactions on Medical Robotics and Bionics (2024) Vol. 6, Iss. 3, pp. 1125-1134
Closed Access | Times Cited: 2
BioMAT: An Open-Source Biomechanics Multi-Activity Transformer for Joint Kinematic Predictions Using Wearable Sensors
Mohsen Sharifi-Renani, Mohammad H. Mahoor, Chadd W. Clary
Sensors (2023) Vol. 23, Iss. 13, pp. 5778-5778
Open Access | Times Cited: 6
Personalized Machine Learning Approach to Estimating Knee Kinematics Using Only Shank-Mounted IMU
Ted Yeung, Astrid Cantamessa, Andreas W. Kempa-Liehr, et al.
IEEE Sensors Journal (2023) Vol. 23, Iss. 11, pp. 12380-12387
Open Access | Times Cited: 5
Deep learning to combat knee osteoarthritis and severity assessment by using CNN-based classification
Suman Rani, Minakshi Memoria, Ahmad Almogren, et al.
BMC Musculoskeletal Disorders (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Deep-learning model for the prediction of lower-limb joint moments using single inertial measurement unit during different locomotive activities
Wenqi Liang, Fanjie Wang, Ao Fan, et al.
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105372-105372
Closed Access | Times Cited: 4
The Effect of IMU Sensor Location, Number of Features, and Window Size on a Random Forest Model’s Accuracy in Predicting Joint Kinematics and Kinetics During Gait
Shima Mohammadi Moghadam, Ted Yeung, Julie Choisne
IEEE Sensors Journal (2023) Vol. 23, Iss. 22, pp. 28328-28339
Closed Access | Times Cited: 4
Dynamic Modelling and Simulation of Industrial Plant Fire and Gas Detection Systems; Parametric Analysis of Nozzle Flow
Anacleto M. Cortez Jr. -, April Joy D. Dumagpi -
International Journal For Multidisciplinary Research (2024) Vol. 6, Iss. 1
Open Access
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