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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:

Current state of digital signal processing in myoelectric interfaces and related applications
Maria Hakonen, Harri Piitulainen, Arto Visala
Biomedical Signal Processing and Control (2015) Vol. 18, pp. 334-359
Open Access | Times Cited: 273

Showing 1-25 of 273 citing articles:

Gesture recognition by instantaneous surface EMG images
Weidong Geng, Yu Du, Wenguang Jin, et al.
Scientific Reports (2016) Vol. 6, Iss. 1
Open Access | Times Cited: 516
Health monitoring through wearable technologies for older adults: Smart wearables acceptance model
Junde Li, Qi Ma, Alan H. S. Chan, et al.
Applied Ergonomics (2018) Vol. 75, pp. 162-169
Closed Access | Times Cited: 346
A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition
Yu Hu, Yongkang Wong, Wentao Wei, et al.
PLoS ONE (2018) Vol. 13, Iss. 10, pp. e0206049-e0206049
Open Access | Times Cited: 326
A review on EMG-based motor intention prediction of continuous human upper limb motion for human-robot collaboration
Luzheng Bi, Aberham Genetu Feleke, Cuntai Guan
Biomedical Signal Processing and Control (2019) Vol. 51, pp. 113-127
Closed Access | Times Cited: 310
Combined influence of forearm orientation and muscular contraction on EMG pattern recognition
Rami N. Khushaba, Ali H. Al‐Timemy, Sarath Kodagoda, et al.
Expert Systems with Applications (2016) Vol. 61, pp. 154-161
Open Access | Times Cited: 175
A review of the key technologies for sEMG-based human-robot interaction systems
Kexiang Li, Jianhua Zhang, Lingfeng Wang, et al.
Biomedical Signal Processing and Control (2020) Vol. 62, pp. 102074-102074
Closed Access | Times Cited: 156
Support Vector Machine-Based EMG Signal Classification Techniques: A Review
Diana C. Toledo-Pérez, Juvenal Rodríguez‐Reséndiz, Roberto A. Gómez‐Loenzo, et al.
Applied Sciences (2019) Vol. 9, Iss. 20, pp. 4402-4402
Open Access | Times Cited: 146
Electromyography Monitoring Systems in Rehabilitation: A Review of Clinical Applications, Wearable Devices and Signal Acquisition Methodologies
Muhammad Al-Ayyad, Hamza Abu Owida, Roberto De Fazio, et al.
Electronics (2023) Vol. 12, Iss. 7, pp. 1520-1520
Open Access | Times Cited: 61
Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies
Usman Asad, Madeeha Khan, Azfar Khalid, et al.
Sensors (2023) Vol. 23, Iss. 8, pp. 3938-3938
Open Access | Times Cited: 58
Intelligent EMG Pattern Recognition Control Method for Upper-Limb Multifunctional Prostheses: Advances, Current Challenges, and Future Prospects
Oluwarotimi Williams Samuel, Mojisola Grace Asogbon, Yanjuan Geng, et al.
IEEE Access (2019) Vol. 7, pp. 10150-10165
Open Access | Times Cited: 143
Rationale, Implementation and Evaluation of Assistive Strategies for an Active Back-Support Exoskeleton
Stefano Toxiri, Axel S. Koopman, Maria Lazzaroni, et al.
Frontiers in Robotics and AI (2018) Vol. 5
Open Access | Times Cited: 138
Robust EMG pattern recognition in the presence of confounding factors: features, classifiers and adaptive learning
Yikun Gu, Dapeng Yang, Qi Huang, et al.
Expert Systems with Applications (2017) Vol. 96, pp. 208-217
Closed Access | Times Cited: 119
Repeatability of grasp recognition for robotic hand prosthesis control based on sEMG data
Francesca Palermo, Matteo Cognolato, Arjan Gijsberts, et al.
(2017), pp. 1154-1159
Closed Access | Times Cited: 99
Myoelectric Interfaces and Related Applications: Current State of EMG Signal Processing–A Systematic Review
Bernabé Rodríguez-Tapia, Israel Soto, Daniela M. Martínez, et al.
IEEE Access (2020) Vol. 8, pp. 7792-7805
Open Access | Times Cited: 96
Understanding Factors Influencing Elderly Diabetic Patients’ Continuance Intention to Use Digital Health Wearables: Extending the Technology Acceptance Model (TAM)
Ashfaq Ahmad, Tareq Rasul, Anish Yousaf, et al.
Journal of Open Innovation Technology Market and Complexity (2020) Vol. 6, Iss. 3, pp. 81-81
Open Access | Times Cited: 78
Feature selection and dimensionality reduction: An extensive comparison in hand gesture classification by sEMG in eight channels armband approach
José Jair Alves Mendes, Melissa La Banca Freitas, Hugo Valadares Siqueira, et al.
Biomedical Signal Processing and Control (2020) Vol. 59, pp. 101920-101920
Closed Access | Times Cited: 72
A Review of Techniques for Surface Electromyography Signal Quality Analysis
Emma Farago, Dawn MacIsaac, Michelle Suk, et al.
IEEE Reviews in Biomedical Engineering (2022) Vol. 16, pp. 472-486
Closed Access | Times Cited: 49
Development of an EMG-Controlled Knee Exoskeleton to Assist Home Rehabilitation in a Game Context
Mingxing Lyu, Wei-Hai Chen, Xilun Ding, et al.
Frontiers in Neurorobotics (2019) Vol. 13
Open Access | Times Cited: 71
putEMG—A Surface Electromyography Hand Gesture Recognition Dataset
Piotr Kaczmarek, Tomasz Mańkowski, Jakub Tomczyński
Sensors (2019) Vol. 19, Iss. 16, pp. 3548-3548
Open Access | Times Cited: 68
Prosthetic hand control: A multidisciplinary review to identify strengths, shortcomings, and the future
Dinesh Kumar, Beth Jelfs, Xiaohong Sui, et al.
Biomedical Signal Processing and Control (2019) Vol. 53, pp. 101588-101588
Closed Access | Times Cited: 65
A Low-Cost, Wireless, 3-D-Printed Custom Armband for sEMG Hand Gesture Recognition
Ulysse Côté‐Allard, Gabriel Gagnon-Turcotte, François Laviolette, et al.
Sensors (2019) Vol. 19, Iss. 12, pp. 2811-2811
Open Access | Times Cited: 63
High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network
Jiangcheng Chen, Sheng Bi, George Zhang, et al.
Sensors (2020) Vol. 20, Iss. 4, pp. 1201-1201
Open Access | Times Cited: 63
An Improved Performance of Deep Learning Based on Convolution Neural Network to Classify the Hand Motion by Evaluating Hyper Parameter
Triwiyanto Triwiyanto, I Putu Alit Pawana, Mauridhi Hery Purnomo
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 28, Iss. 7, pp. 1678-1688
Closed Access | Times Cited: 56
Surface EMG-Based Instantaneous Hand Gesture Recognition Using Convolutional Neural Network with the Transfer Learning Method
Zhipeng Yu, Jianghai Zhao, Yucheng Wang, et al.
Sensors (2021) Vol. 21, Iss. 7, pp. 2540-2540
Open Access | Times Cited: 42
sEMG time–frequency features for hand movements classification
Somar Karheily, Ali Moukadem, Jean‐Baptiste Courbot, et al.
Expert Systems with Applications (2022) Vol. 210, pp. 118282-118282
Open Access | Times Cited: 36
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