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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:

Electromyography data for non-invasive naturally-controlled robotic hand prostheses
Manfredo Atzori, Arjan Gijsberts, Claudio Castellini, et al.
Scientific Data (2014) Vol. 1, Iss. 1
Open Access | Times Cited: 760

Showing 26-50 of 760 citing articles:

EMGHandNet: A hybrid CNN and Bi-LSTM architecture for hand activity classification using surface EMG signals
Naveen Kumar Karnam, Shiv Ram Dubey, Anish C. Turlapaty, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 1, pp. 325-340
Closed Access | Times Cited: 91
Surface Electromyography as a Natural Human–Machine Interface: A Review
Mingde Zheng, Michael S. Crouch, Michael S. Eggleston
IEEE Sensors Journal (2022) Vol. 22, Iss. 10, pp. 9198-9214
Open Access | Times Cited: 73
An Artificial Neuromuscular System for Bimodal Human–Machine Interaction
Sunyingyue Geng, Shuangqing Fan, Hangfei Li, et al.
Advanced Functional Materials (2023) Vol. 33, Iss. 31
Closed Access | Times Cited: 44
Deep learning-based artificial vision for grasp classification in myoelectric hands
Ghazal Ghazaei, Ali Alameer, Patrick Degenaar, et al.
Journal of Neural Engineering (2017) Vol. 14, Iss. 3, pp. 036025-036025
Open Access | Times Cited: 164
Control Capabilities of Myoelectric Robotic Prostheses by Hand Amputees: A Scientific Research and Market Overview
Manfredo Atzori, Henning Müller
Frontiers in Systems Neuroscience (2015) Vol. 9
Open Access | Times Cited: 163
Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic Computing
Enea Ceolini, Charlotte Frenkel, Sumit Bam Shrestha, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 137
An experimental study on upper limb position invariant EMG signal classification based on deep neural network
Anand Kumar Mukhopadhyay, Suman Samui
Biomedical Signal Processing and Control (2019) Vol. 55, pp. 101669-101669
Closed Access | Times Cited: 128
Force Myography to Control Robotic Upper Extremity Prostheses: A Feasibility Study
Erina Cho, Richard J. Chen, Lukas-Karim Merhi, et al.
Frontiers in Bioengineering and Biotechnology (2016) Vol. 4
Open Access | Times Cited: 125
Robust Real-Time Embedded EMG Recognition Framework Using Temporal Convolutional Networks on a Multicore IoT Processor
Marcello Zanghieri, Simone Benatti, Alessio Burrello, et al.
IEEE Transactions on Biomedical Circuits and Systems (2019) Vol. 14, Iss. 2, pp. 244-256
Open Access | Times Cited: 116
High-Density Electromyography and Motor Skill Learning for Robust Long-Term Control of a 7-DoF Robot Arm
Mark Ison, Ivan Vujaklija, Bryan Whitsell, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2015) Vol. 24, Iss. 4, pp. 424-433
Closed Access | Times Cited: 113
sEMG-Based Gesture Recognition with Convolution Neural Networks
Zhen Ding, Chifu Yang, Zhihong Tian, et al.
Sustainability (2018) Vol. 10, Iss. 6, pp. 1865-1865
Open Access | Times Cited: 110
Toward an Enhanced Human–Machine Interface for Upper-Limb Prosthesis Control With Combined EMG and NIRS Signals
Weichao Guo, Xinjun Sheng, Honghai Liu, et al.
IEEE Transactions on Human-Machine Systems (2017) Vol. 47, Iss. 4, pp. 564-575
Closed Access | Times Cited: 107
A Subject-Transfer Framework Based on Single-Trial EMG Analysis Using Convolutional Neural Networks
Keun-Tae Kim, Cuntai Guan, Seong‐Whan Lee
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 28, Iss. 1, pp. 94-103
Closed Access | Times Cited: 106
FS-HGR: Few-Shot Learning for Hand Gesture Recognition via Electromyography
Elahe Rahimian, Soheil Zabihi, Amir Asif, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 1004-1015
Open Access | Times Cited: 100
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
Causes of Performance Degradation in Non-invasive Electromyographic Pattern Recognition in Upper Limb Prostheses
Iris Kyranou, Sethu Vijayakumar, Mustafa Suphi Erden
Frontiers in Neurorobotics (2018) Vol. 12
Open Access | Times Cited: 98
Assessment of a Wearable Force- and Electromyography Device and Comparison of the Related Signals for Myocontrol
Mathilde Connan, Eduardo Ruiz Ramírez, Bernhard Vodermayer, et al.
Frontiers in Neurorobotics (2016) Vol. 10
Open Access | Times Cited: 92
Design of a Flexible Wearable Smart sEMG Recorder Integrated Gradient Boosting Decision Tree Based Hand Gesture Recognition
Wei Song, Anhe Wang, Yang Chen, et al.
IEEE Transactions on Biomedical Circuits and Systems (2019) Vol. 13, Iss. 6, pp. 1563-1574
Open Access | Times Cited: 85
Gesture recognition based on surface electromyography‐featureimage
Yangwei Cheng, Gongfa Li, Mingchao Yu, et al.
Concurrency and Computation Practice and Experience (2020) Vol. 33, Iss. 6
Closed Access | Times Cited: 84
Hand gesture recognition based on motor unit spike trains decoded from high-density electromyography
Chen Chen, Yang Yu, Shihan Ma, et al.
Biomedical Signal Processing and Control (2019) Vol. 55, pp. 101637-101637
Closed Access | Times Cited: 77
Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings
Xinyu Jiang, Xiangyu Liu, Jiahao Fan, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 1035-1046
Open Access | Times Cited: 76
Advances and Disturbances in sEMG-Based Intentions and Movements Recognition: A Review
Hao Xu, Anbin Xiong
IEEE Sensors Journal (2021) Vol. 21, Iss. 12, pp. 13019-13028
Closed Access | Times Cited: 75
A Transfer Learning Model for Gesture Recognition Based on the Deep Features Extracted by CNN
Yongxiang Zou, Long Cheng
IEEE Transactions on Artificial Intelligence (2021) Vol. 2, Iss. 5, pp. 447-458
Open Access | Times Cited: 59
A Review of Human–Machine Cooperation in the Robotics Domain
Canjun Yang, Yuanchao Zhu, Yanhu Chen
IEEE Transactions on Human-Machine Systems (2021) Vol. 52, Iss. 1, pp. 12-25
Open Access | Times Cited: 58
Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning–A Survey in Myoelectric Control
Tianzhe Bao, Sheng Quan Xie, Pengfei Yang, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 8, pp. 3822-3835
Open Access | Times Cited: 46

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