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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:

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

Showing 1-25 of 119 citing articles:

A wearable biosensing system with in-sensor adaptive machine learning for hand gesture recognition
Ali Moin, Andy Zhou, Abbas Rahimi, et al.
Nature Electronics (2020) Vol. 4, Iss. 1, pp. 54-63
Closed Access | Times Cited: 478
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
A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control
Ali Ameri, Mohammad Ali Akhaee, Erik Scheme, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 28, Iss. 2, pp. 370-379
Closed Access | Times Cited: 124
Classification of Hand Movements based on Discrete Wavelet Transform and Enhanced Feature Extraction
Jingwei Too, Abdul Rahim, Norhashimah Mohd Saad
International Journal of Advanced Computer Science and Applications (2019) Vol. 10, Iss. 6
Open Access | Times Cited: 118
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
Current Trends and Confounding Factors in Myoelectric Control: Limb Position and Contraction Intensity
Evan Campbell, Angkoon Phinyomark, Erik Scheme
Sensors (2020) Vol. 20, Iss. 6, pp. 1613-1613
Open Access | Times Cited: 102
A Review on the Rehabilitation Exoskeletons for the Lower Limbs of the Elderly and the Disabled
Tao Wang, Bin Zhang, Chenhao Liu, et al.
Electronics (2022) Vol. 11, Iss. 3, pp. 388-388
Open Access | Times Cited: 54
A deep learning strategy for EMG-based joint position prediction in hip exoskeleton assistive robots
Ali Foroutannia, Mohammad-R. Akbarzadeh-T, Alireza Akbarzadeh
Biomedical Signal Processing and Control (2022) Vol. 75, pp. 103557-103557
Closed Access | Times Cited: 38
Bio-robotics research for non-invasive myoelectric neural interfaces for upper-limb prosthetic control: a 10-year perspective review
Ning Jiang, Chen Chen, Jiayuan He, et al.
National Science Review (2023) Vol. 10, Iss. 5
Open Access | Times Cited: 31
A Global and Local Feature fused CNN architecture for the sEMG-based hand gesture recognition
Baoping Xiong, Wensheng Chen, Yinxi Niu, et al.
Computers in Biology and Medicine (2023) Vol. 166, pp. 107497-107497
Closed Access | Times Cited: 23
Advances in Machine Learning for Wearable Sensors
Xiao Xiao, Junyi Yin, Jing Xu, et al.
ACS Nano (2024) Vol. 18, Iss. 34, pp. 22734-22751
Closed Access | Times Cited: 11
Surface Electromyography (EMG) Signal Processing, Classification, and Practical Considerations
Angkoon Phinyomark, Evan Campbell, Erik Scheme
Series in bioengineering (2019), pp. 3-29
Closed Access | Times Cited: 67
Decoding Simultaneous Multi-DOF Wrist Movements From Raw EMG Signals Using a Convolutional Neural Network
Wei Yang, Dapeng Yang, Yü Liu, et al.
IEEE Transactions on Human-Machine Systems (2019) Vol. 49, Iss. 5, pp. 411-420
Closed Access | Times Cited: 64
Continuous estimation of upper limb joint angle from sEMG signals based on SCA-LSTM deep learning approach
Chenfei Ma, Chuang Lin, Oluwarotimi Williams Samuel, et al.
Biomedical Signal Processing and Control (2020) Vol. 61, pp. 102024-102024
Closed Access | Times Cited: 63
Identification of a feature selection based pattern recognition scheme for finger movement recognition from multichannel EMG signals
P. Geethanjali, Vikas Raunak
Australasian Physical & Engineering Sciences in Medicine (2018) Vol. 41, Iss. 2, pp. 549-559
Closed Access | Times Cited: 61
Adaptive Hybrid Classifier for Myoelectric Pattern Recognition Against the Interferences of Outlier Motion, Muscle Fatigue, and Electrode Doffing
Qichuan Ding, Xingang Zhao, Jianda Han, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2019) Vol. 27, Iss. 5, pp. 1071-1080
Closed Access | Times Cited: 60
Review on Control Strategies for Lower Limb Rehabilitation Exoskeletons
Wenzhou Li, Guang‐Zhong Cao, Aibin Zhu
IEEE Access (2021) Vol. 9, pp. 123040-123060
Open Access | Times Cited: 54
Dataset for multi-channel surface electromyography (sEMG) signals of hand gestures
Mehmet Akif Özdemir, Deniz Hande Kisa, Onan Güren, et al.
Data in Brief (2022) Vol. 41, pp. 107921-107921
Open Access | Times Cited: 36
Improving the Robustness and Adaptability of sEMG-Based Pattern Recognition Using Deep Domain Adaptation
Ping Shi, Xinran Zhang, Wei Li, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 11, pp. 5450-5460
Closed Access | Times Cited: 30
Optimization of HD-sEMG-Based Cross-Day Hand Gesture Classification by Optimal Feature Extraction and Data Augmentation
Xinyu Jiang, Xiangyu Liu, Jiahao Fan, et al.
IEEE Transactions on Human-Machine Systems (2022) Vol. 52, Iss. 6, pp. 1281-1291
Closed Access | Times Cited: 29
Understanding the influence of confounding factors in myoelectric control for discrete gesture recognition
Ethan Eddy, Evan Campbell, Scott Bateman, et al.
Journal of Neural Engineering (2024) Vol. 21, Iss. 3, pp. 036015-036015
Open Access | Times Cited: 6
Biometric From Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition
Jiayuan He, Ning Jiang
Frontiers in Bioengineering and Biotechnology (2020) Vol. 8
Open Access | Times Cited: 49
Selection of Features and Classifiers for EMG-EEG-Based Upper Limb Assistive Devices—A Review
Salman Mohd Khan, Abid Ali Khan, Omar Farooq
IEEE Reviews in Biomedical Engineering (2019) Vol. 13, pp. 248-260
Closed Access | Times Cited: 48
Unsupervised Domain Adversarial Self-Calibration for Electromyography-Based Gesture Recognition
Ulysse Côté‐Allard, Gabriel Gagnon-Turcotte, Angkoon Phinyomark, et al.
IEEE Access (2020) Vol. 8, pp. 177941-177955
Open Access | Times Cited: 48
Shoulder muscle activation pattern recognition based on sEMG and machine learning algorithms
Yongyu Jiang, Christine Chen, Xiaodong Zhang, et al.
Computer Methods and Programs in Biomedicine (2020) Vol. 197, pp. 105721-105721
Closed Access | Times Cited: 48
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