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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:

Prediction of ground reaction forces for Parkinson's disease patients using a kinect-driven musculoskeletal gait analysis model
Moataz Eltoukhy, Christopher Kuenze, Michael Skipper Andersen, et al.
Medical Engineering & Physics (2017) Vol. 50, pp. 75-82
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Three-dimensional cameras and skeleton pose tracking for physical function assessment: A review of uses, validity, current developments and Kinect alternatives
Ross A. Clark, Benjamin F. Mentiplay, Emma Hough, et al.
Gait & Posture (2018) Vol. 68, pp. 193-200
Closed Access | Times Cited: 181
Recent advances in rehabilitation for Parkinson’s Disease with Exergames: A Systematic Review
Augusto García-Agúndez, Ann‐Kristin Folkerts, Robert Konrad, et al.
Journal of NeuroEngineering and Rehabilitation (2019) Vol. 16, Iss. 1
Open Access | Times Cited: 147
Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture
Angelos Karatsidis, Moonki Jung, H. Martin Schepers, et al.
Medical Engineering & Physics (2019) Vol. 65, pp. 68-77
Open Access | Times Cited: 110
Biomechanics Parameters of Gait Analysis to Characterize Parkinson’s Disease: A Scoping Review
Michela Russo, Marianna Amboni, Noemi Pisani, et al.
Sensors (2025) Vol. 25, Iss. 2, pp. 338-338
Open Access | Times Cited: 1
On the Modeling of Biomechanical Systems for Human Movement Analysis: A Narrative Review
Ivo Roupa, Mariana Silva, Filipe Marques, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 7, pp. 4915-4958
Closed Access | Times Cited: 30
Evaluation of ground reaction forces and centers of pressure predicted by AnyBody Modeling System during load reaching/handling activities and effects of the prediction errors on model-estimated spinal loads
Sajjad Daroudi, Navid Arjmand, Mahdi Mohseni, et al.
Journal of Biomechanics (2024) Vol. 164, pp. 111974-111974
Closed Access | Times Cited: 6
Using Kinect to classify Parkinson’s disease stages related to severity of gait impairment
Lacramioara Dranca, Lopez de Abetxuko Ruiz de Mendarozketa, Alfredo Goñi, et al.
BMC Bioinformatics (2018) Vol. 19, Iss. 1
Open Access | Times Cited: 51
Computer-Vision Based Diagnosis of Parkinson’s Disease via Gait: A Survey
Navleen Kour, Sunanda Sunanda, Sakshi Arora
IEEE Access (2019) Vol. 7, pp. 156620-156645
Open Access | Times Cited: 47
Prediction of ground reaction force and joint moments based on optical motion capture data during gait
Marion Mundt, Arnd Koeppe, Sina David, et al.
Medical Engineering & Physics (2020) Vol. 86, pp. 29-34
Closed Access | Times Cited: 46
Classification, Prediction, and Monitoring of Parkinson’s disease using Computer Assisted Technologies: A Comparative Analysis
Jinee Goyal, Padmavati Khandnor, Trilok Chand Aseri
Engineering Applications of Artificial Intelligence (2020) Vol. 96, pp. 103955-103955
Closed Access | Times Cited: 42
Ground reaction force and joint moment estimation during gait using an Azure Kinect-driven musculoskeletal modeling approach
Zachary Ripic, Christopher Kuenze, Michael Skipper Andersen, et al.
Gait & Posture (2022) Vol. 95, pp. 49-55
Closed Access | Times Cited: 22
A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait
Zachary Ripic, M. B. Nienhuis, Joseph F. Signorile, et al.
Journal of Biomechanics (2023) Vol. 159, pp. 111793-111793
Closed Access | Times Cited: 15
Multibody dynamics-based musculoskeletal modeling for gait analysis: a systematic review
Muhammad Abdullah, Abdul Aziz Hulleck, Rateb Katmah, et al.
Journal of NeuroEngineering and Rehabilitation (2024) Vol. 21, Iss. 1
Open Access | Times Cited: 5
Bilateral Ground Reaction Force Prediction Using Deep Learning Models and Custom Force Plate
Y. H. Yeo, Muhammad Fauzinizam Razali, Zaidi Mohd Ripin, et al.
IIUM Engineering Journal (2025) Vol. 26, Iss. 1, pp. 524-548
Open Access
Psychological and physiological computing based on multi-dimensional foot information
Shengyang Li, Huilin Yao, Ruotian Peng, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 5
Open Access
Prediction of human walking vertical load based on markerless human gait capture using multi-view cameras and LSTM network
Huiqi Liang, Wenbo Xie, Yijing Lu, et al.
Engineering Structures (2025) Vol. 334, pp. 120228-120228
Closed Access
Prediction of ground reaction forces and moments during walking in children with cerebral palsy
Julie Kloeckner, Rosa M. S. Visscher, William R. Taylor, et al.
Frontiers in Human Neuroscience (2023) Vol. 17
Open Access | Times Cited: 11
All Knitted and Integrated Soft Wearable of High Stretchability and Sensitivity for Continuous Monitoring of Human Joint Motion
Ujjaval Gupta, Jun Liang Lau, Pei Zhi Chia, et al.
Advanced Healthcare Materials (2023) Vol. 12, Iss. 21
Closed Access | Times Cited: 11
Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson’s disease
Zachary Ripic, Joseph F. Signorile, Thomas M. Best, et al.
Journal of Biomechanics (2023) Vol. 155, pp. 111645-111645
Closed Access | Times Cited: 11
Markerless motion capture provides accurate predictions of ground reaction forces across a range of movement tasks
Glen A. Lichtwark, Robert W. Schuster, Luke A. Kelly, et al.
Journal of Biomechanics (2024) Vol. 166, pp. 112051-112051
Open Access | Times Cited: 4
Prediction of gait kinetics using Markerless-driven musculoskeletal modeling
Zachary Ripic, Ilias Theodorakos, Michael Skipper Andersen, et al.
Journal of Biomechanics (2023) Vol. 157, pp. 111712-111712
Closed Access | Times Cited: 9
Marker-less versus marker-based driven musculoskeletal models of the spine during static load-handling activities
Farkhondeh Asadi, Navid Arjmand
Journal of Biomechanics (2020) Vol. 112, pp. 110043-110043
Closed Access | Times Cited: 27
A forward-inverse dynamics modeling framework for human musculoskeletal multibody system
Xinyue Wang, Jianqiao Guo, Qiang Tian
Acta Mechanica Sinica (2022) Vol. 38, Iss. 11
Closed Access | Times Cited: 15
Statistical methods for analysis of Parkinson’s disease gait pattern and classification
Anup Nandy
Multimedia Tools and Applications (2019) Vol. 78, Iss. 14, pp. 19697-19734
Closed Access | Times Cited: 25
Motion acquisition of gait characteristics one week after total hip arthroplasty: a factor analysis
Andrea Cattaneo, Anna Ghidotti, Francesco Catellani, et al.
Archives of Orthopaedic and Trauma Surgery (2024) Vol. 144, Iss. 5, pp. 2347-2356
Open Access | Times Cited: 2
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