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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:

Feature extraction via KPCA for classification of gait patterns
Jianning Wu, Jue Wang, Li Liu
Human Movement Science (2007) Vol. 26, Iss. 3, pp. 393-411
Closed Access | Times Cited: 103

Showing 1-25 of 103 citing articles:

A survey on wearable sensor modality centred human activity recognition in health care
Yan Wang, Shuang Cang, Hongnian Yu
Expert Systems with Applications (2019) Vol. 137, pp. 167-190
Open Access | Times Cited: 311
Computational Intelligence in Gait Research: A Perspective on Current Applications and Future Challenges
Daniel Lai, Rezaul Begg, Marimuthu Palaniswami
IEEE Transactions on Information Technology in Biomedicine (2009) Vol. 13, Iss. 5, pp. 687-702
Closed Access | Times Cited: 148
Recognition of Affect Based on Gait Patterns
Michelle Karg, Kolja Kühnlenz, Martin Buss
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (2010) Vol. 40, Iss. 4, pp. 1050-1061
Closed Access | Times Cited: 145
Automatic recognition of gait patterns in human motor disorders using machine learning: A review
Joana Figueiredo, Cristina P. Santos, Juan C. Moreno
Medical Engineering & Physics (2018) Vol. 53, pp. 1-12
Open Access | Times Cited: 137
Evaluation of driver fatigue on two channels of EEG data
Wei Li, Qichang He, Xiumin Fan, et al.
Neuroscience Letters (2011) Vol. 506, Iss. 2, pp. 235-239
Closed Access | Times Cited: 131
Nonlinear feature selection using Gaussian kernel SVM-RFE for fault diagnosis
Yangtao Xue, Li Zhang, Bangjun Wang, et al.
Applied Intelligence (2018) Vol. 48, Iss. 10, pp. 3306-3331
Closed Access | Times Cited: 85
Classification of Gait Type Based on Deep Learning Using Various Sensors with Smart Insole
Sung-Sin Lee, Sang Tae Choi, Sang‐Il Choi
Sensors (2019) Vol. 19, Iss. 8, pp. 1757-1757
Open Access | Times Cited: 74
The detection of age groups by dynamic gait outcomes using machine learning approaches
Yuhan Zhou, Robbin Romijnders, Clint Hansen, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 57
GaitRec, a large-scale ground reaction force dataset of healthy and impaired gait
Brian Horsak, Djordje Slijepčević, Anna-Maria Raberger, et al.
Scientific Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 56
Method of fault feature selection and fusion based on poll mode and optimized weighted KPCA for bearings
Junxian Shen, Feiyun Xu
Measurement (2022) Vol. 194, pp. 110950-110950
Closed Access | Times Cited: 29
Diagnosing fatigue in gait patterns by support vector machines and self-organizing maps
Daniël Janssen, Wolfgang I. Schöllhorn, Karl M. Newell, et al.
Human Movement Science (2010) Vol. 30, Iss. 5, pp. 966-975
Closed Access | Times Cited: 77
Gait patterns of asymmetric ankle osteoarthritis patients
Corina Nüesch, Víctor Valderrábano, Cora Huber, et al.
Clinical Biomechanics (2012) Vol. 27, Iss. 6, pp. 613-618
Closed Access | Times Cited: 67
A new approach for fault diagnosis with full-scope simulator based on state information imaging in nuclear power plant
Yuantao Yao, Jin Wang, Min Xie, et al.
Annals of Nuclear Energy (2020) Vol. 141, pp. 107274-107274
Closed Access | Times Cited: 43
Recent use of deep learning techniques in clinical applications based on gait: a survey
Yume Matsushita, Dinh Tuan Tran, Hirotake Yamazoe, et al.
Journal of Computational Design and Engineering (2021) Vol. 8, Iss. 6, pp. 1499-1532
Open Access | Times Cited: 32
A novel graph-based hybrid deep learning of cumulative GRU and deeper GCN for recognition of abnormal gait patterns using wearable sensors
Jianning Wu, Jie‐Sheng Huang, Xiaoyan Wu, et al.
Expert Systems with Applications (2023) Vol. 233, pp. 120968-120968
Closed Access | Times Cited: 15
Marker-based classification of young–elderly gait pattern differences via direct PCA feature extraction and SVMs
Bjoern M. Eskofier, Peter Federolf, Patrick Kugler, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2011) Vol. 16, Iss. 4, pp. 435-442
Open Access | Times Cited: 55
Pattern classification of kinematic and kinetic running data to distinguish gender, shod/barefoot and injury groups with feature ranking
Bjoern M. Eskofier, Martin F. Kraus, Jay T. Worobets, et al.
Computer Methods in Biomechanics & Biomedical Engineering (2011) Vol. 15, Iss. 5, pp. 467-474
Closed Access | Times Cited: 49
Defining functional groups based on running kinematics using Self-Organizing Maps and Support Vector Machines
Stefan Hoerzer, Vinzenz von Tscharner, Christian Jacob, et al.
Journal of Biomechanics (2015) Vol. 48, Iss. 10, pp. 2072-2079
Closed Access | Times Cited: 49
Do intermediate- and higher-order principal components contain useful information to detect subtle changes in lower extremity biomechanics during running?
Angkoon Phinyomark, Blayne A. Hettinga, Sean T. Osis, et al.
Human Movement Science (2015) Vol. 44, pp. 91-101
Closed Access | Times Cited: 45
Ankle plantarflexion strength in rearfoot and forefoot runners: A novel clusteranalytic approach
Dominik Liebl, Steffen Willwacher, Joseph Hamill, et al.
Human Movement Science (2014) Vol. 35, pp. 104-120
Closed Access | Times Cited: 44
Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning
Zhengyang Lan, Mathieu Lempereur, Gwenael Gueret, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108095-108095
Open Access | Times Cited: 3
Automatic Classification of Functional Gait Disorders
Djordje Slijepčević, Matthias Zeppelzauer, Anna‐Maria Gorgas, et al.
IEEE Journal of Biomedical and Health Informatics (2017) Vol. 22, Iss. 5, pp. 1653-1661
Open Access | Times Cited: 39
Selection of clinical features for pattern recognition applied to gait analysis
Rosa Altilio, Marco Paoloni, Massimo Panella
Medical & Biological Engineering & Computing (2016) Vol. 55, Iss. 4, pp. 685-695
Closed Access | Times Cited: 35
Characterization and Identification of Coal and Carbonaceous Shale Using Visible and Near-Infrared Reflectance Spectroscopy
En Yang, Shirong Ge, Shibo Wang
Journal of Spectroscopy (2018) Vol. 2018, pp. 1-13
Open Access | Times Cited: 34
Machine learning-based classification of healthy and impaired gaits using 3D-GRF signals
Md Nazmul Islam Shuzan, Muhammad E. H. Chowdhury, Mamun Bin Ibne Reaz, et al.
Biomedical Signal Processing and Control (2022) Vol. 81, pp. 104448-104448
Closed Access | Times Cited: 16
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