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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:

A Novel Classification Strategy to Distinguish Five Levels of Pain Using the EEG Signal Features
Tahereh Nezam, Reza Boostani, Vahid Abootalebi, et al.
IEEE Transactions on Affective Computing (2018) Vol. 12, Iss. 1, pp. 131-140
Closed Access | Times Cited: 43

Showing 1-25 of 43 citing articles:

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives
Marco Cascella, Daniela Schiavo, Arturo Cuomo, et al.
Pain Research and Management (2023) Vol. 2023, pp. 1-13
Open Access | Times Cited: 47
Decoding Pain: A Comprehensive Review of Computational Intelligence Methods in Electroencephalography-Based Brain–Computer Interfaces
Hadeel Alshehri, Abeer Al-Nafjan, Mashael Aldayel
Diagnostics (2025) Vol. 15, Iss. 3, pp. 300-300
Open Access | Times Cited: 1
Objective Pain Assessment Using Deep Learning Through EEG-Based Brain–Computer Interfaces
Abeer Al-Nafjan, Hadeel Alshehri, Mashael Aldayel
Biology (2025) Vol. 14, Iss. 2, pp. 210-210
Open Access | Times Cited: 1
Scalp EEG-Based Pain Detection Using Convolutional Neural Network
Duo Chen, Haihong Zhang, Perumpadappil Thomas Kavitha, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 30, pp. 274-285
Open Access | Times Cited: 31
Feature Extraction and Selection for Pain Recognition Using Peripheral Physiological Signals
Evan Campbell, Angkoon Phinyomark, Erik Scheme
Frontiers in Neuroscience (2019) Vol. 13
Open Access | Times Cited: 49
A Spatiotemporal Deep Learning Framework for Scalp EEG-Based Automated Pain Assessment in Children
Zanhao Fu, Huaiyu Zhu, Yi Zhang, et al.
IEEE Transactions on Biomedical Engineering (2024) Vol. 71, Iss. 6, pp. 1889-1900
Closed Access | Times Cited: 5
EEG frequency band analysis in chronic neuropathic pain: A linear and nonlinear approach to classify pain severity
Daniela M. Zolezzi, Luz María Alonso-Valerdi, David I. Ibarra-Zárate
Computer Methods and Programs in Biomedicine (2023) Vol. 230, pp. 107349-107349
Open Access | Times Cited: 12
Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain
Giuseppe Valerio Aurucci, Greta Preatoni, Arianna Damiani, et al.
Neurotherapeutics (2023) Vol. 20, Iss. 5, pp. 1316-1329
Open Access | Times Cited: 11
Unraveling the physiological and psychosocial signatures of pain by machine learning
Noemi Gozzi, Greta Preatoni, Federico Ciotti, et al.
Med (2024)
Open Access | Times Cited: 4
Friction-induced pain: from skin surface to brain activation
Xingxing Fang, Wei Tang, Shousheng Zhang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2025) Vol. 33, pp. 532-541
Open Access
A novel channel selection approach for human neonate’s pain EEG data analysis
Safa Talebi, Javad Frounchi, Behzad Mozaffari Tazehkand
Signal Image and Video Processing (2025) Vol. 19, Iss. 5
Closed Access
Pain and the Brain: A Systematic Review of Methods, EEG Biomarkers, Limitations, and Future Directions
Bayan Ahmad, Buket D. Barkana
Neurology International (2025) Vol. 17, Iss. 4, pp. 46-46
Open Access
Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals
Imran Razzak, Ibrahim A. Hameed, Guandong Xu
IEEE Journal of Translational Engineering in Health and Medicine (2019) Vol. 7, pp. 1-8
Open Access | Times Cited: 31
Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals
İrem Taşçı, Mehmet Bayğın, Prabal Datta Barua, et al.
Cognitive Neurodynamics (2024) Vol. 18, Iss. 5, pp. 2193-2210
Open Access | Times Cited: 3
Quantification of pain severity using EEG-based functional connectivity
P. Modares-Haghighi, Reza Boostani, Mohammad Nami, et al.
Biomedical Signal Processing and Control (2021) Vol. 69, pp. 102840-102840
Open Access | Times Cited: 20
Systematic Review of the Effectiveness of Machine Learning Algorithms for Classifying Pain Intensity, Phenotype or Treatment Outcomes Using Electroencephalogram Data
Tyler Mari, J.R. Henderson, Michelle Maden, et al.
Journal of Pain (2021) Vol. 23, Iss. 3, pp. 349-369
Open Access | Times Cited: 19
An EEG based hierarchical classification strategy to differentiate five intensities of pain
Somayeh Afrasiabi, Reza Boostani, Mohammad Ali Masnadi‐Shirazi, et al.
Expert Systems with Applications (2021) Vol. 180, pp. 115010-115010
Closed Access | Times Cited: 14
Cloud Computing to Fog Computing: A Paradigm Shift
Syed Rizwan Hassan, Muhammad Rashad
IntechOpen eBooks (2023)
Open Access | Times Cited: 5
Semantic Segmentation of Periocular Near-Infra-Red Eye Images Under Alcohol Effects
Juan Tapia, Enrique López Droguett, Andrés Valenzuela, et al.
IEEE Access (2021) Vol. 9, pp. 109732-109744
Open Access | Times Cited: 11
A deep learning-based comprehensive robotic system for lower limb rehabilitation
Prithwijit Mukherjee, Anisha Halder Roy
Biomedical Signal Processing and Control (2024) Vol. 100, pp. 107178-107178
Closed Access | Times Cited: 1
Automated Assessment of Pain Intensity Based on EEG Signal Analysis
Panos Bonotis, Dimosthenis C. Tsouros, Panagiotis N. Smyrlis, et al.
(2019)
Closed Access | Times Cited: 11
Learning Spatial-Spectral-Temporal EEG Representations with Deep Attentive-Recurrent-Convolutional Neural Networks for Pain Intensity Assessment
Fengjie Wu, Weijian Mai, Yisheng Tang, et al.
Neuroscience (2021) Vol. 481, pp. 144-155
Closed Access | Times Cited: 8
Painometry
Hoang Truong, Nam Bui, Zohreh Raghebi, et al.
(2020), pp. 419-433
Closed Access | Times Cited: 6
A Physiological-Inspired Classification Strategy to Classify Five Levels of Pain
Somayeh Afrasiabi, Reza Boostani, M.A. Masnadi-Shirazi
(2019) Vol. 5, pp. 106-111
Closed Access | Times Cited: 5
Differentiation of pain levels by deploying various electroencephalogram synchronization features and a dynamic ensemble selection mechanism
Somayeh Afrasiabi, Reza Boostani, M.A. Masnadi-Shirazi
Physiological Measurement (2020) Vol. 41, Iss. 11, pp. 115004-115004
Closed Access | Times Cited: 4
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