Natasha Padfield

734 total citations · 1 hit paper
8 papers, 477 citations indexed

About

Natasha Padfield is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Electrical and Electronic Engineering. According to data from OpenAlex, Natasha Padfield has authored 8 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Cognitive Neuroscience, 5 papers in Cellular and Molecular Neuroscience and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Natasha Padfield's work include EEG and Brain-Computer Interfaces (7 papers), Neuroscience and Neural Engineering (5 papers) and Advanced Memory and Neural Computing (3 papers). Natasha Padfield is often cited by papers focused on EEG and Brain-Computer Interfaces (7 papers), Neuroscience and Neural Engineering (5 papers) and Advanced Memory and Neural Computing (3 papers). Natasha Padfield collaborates with scholars based in United Kingdom, Malta and China. Natasha Padfield's co-authors include Huimin Zhao, Jinchang Ren, Valentín Masero, Jaime Zabalza, Kenneth P. Camilleri, Marvin K. Bugeja, Tracey Camilleri, Simon G. Fabri, Paul Murray and Jiangbin Zheng and has published in prestigious journals such as Sensors, Neurocomputing and IEEE Journal of Biomedical and Health Informatics.

In The Last Decade

Natasha Padfield

6 papers receiving 463 citations

Hit Papers

EEG-Based Brain-Computer Interfaces Using Motor-Imagery: ... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Natasha Padfield United Kingdom 6 412 182 103 101 85 8 477
Karl McCreadie United Kingdom 11 537 1.3× 231 1.3× 123 1.2× 142 1.4× 103 1.2× 25 603
Moonyoung Kwon South Korea 12 506 1.2× 152 0.8× 99 1.0× 101 1.0× 56 0.7× 22 573
Eduardo Santamaría-Vázquez Spain 12 393 1.0× 137 0.8× 68 0.7× 120 1.2× 53 0.6× 28 475
Minmin Miao China 13 327 0.8× 140 0.8× 92 0.9× 78 0.8× 95 1.1× 27 412
Shefa A. Dawwd Iraq 7 330 0.8× 128 0.7× 105 1.0× 129 1.3× 65 0.8× 25 426
Ali Al-Saegh Iraq 5 336 0.8× 131 0.7× 86 0.8× 117 1.2× 69 0.8× 13 377
Xiangmin Lun China 6 313 0.8× 127 0.7× 83 0.8× 101 1.0× 62 0.7× 17 384
Víctor Martínez-Cagigal Spain 13 433 1.1× 173 1.0× 101 1.0× 131 1.3× 54 0.6× 29 481

Countries citing papers authored by Natasha Padfield

Since Specialization
Citations

This map shows the geographic impact of Natasha Padfield's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Natasha Padfield with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natasha Padfield more than expected).

Fields of papers citing papers by Natasha Padfield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natasha Padfield. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Natasha Padfield. The network helps show where Natasha Padfield may publish in the future.

Co-authorship network of co-authors of Natasha Padfield

This figure shows the co-authorship network connecting the top 25 collaborators of Natasha Padfield. A scholar is included among the top collaborators of Natasha Padfield based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Natasha Padfield. Natasha Padfield is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Peng, Yong, Jiangchuan Liu, Natasha Padfield, et al.. (2025). Prediction Consistency and Confidence-Based Proxy Domain Construction for Privacy-Preserving in Cross-Subject EEG Classification. IEEE Journal of Biomedical and Health Informatics. 30(2). 1115–1127.
2.
Padfield, Natasha, Tracey Camilleri, Simon G. Fabri, Marvin K. Bugeja, & Kenneth P. Camilleri. (2024). A combined EEG motor and speech imagery paradigm with automated successive halving for customizable command selection. OAR@UM (University of Malta). 11(3). 125–142.
3.
Padfield, Natasha, et al.. (2023). BCI-controlled wheelchairs: end-users’ perceptions, needs, and expectations, an interview-based study. Disability and Rehabilitation Assistive Technology. 19(4). 1539–1551. 6 indexed citations
4.
Padfield, Natasha, Kenneth P. Camilleri, Tracey Camilleri, Simon G. Fabri, & Marvin K. Bugeja. (2022). A Comprehensive Review of Endogenous EEG-Based BCIs for Dynamic Device Control. Sensors. 22(15). 5802–5802. 35 indexed citations
5.
Padfield, Natasha, et al.. (2021). Multi-segment Majority Voting Decision Fusion for MI EEG Brain-Computer Interfacing. Cognitive Computation. 13(6). 1484–1495. 13 indexed citations
6.
Padfield, Natasha, Jinchang Ren, Paul Murray, & Huimin Zhao. (2021). Sparse learning of band power features with genetic channel selection for effective classification of EEG signals. Neurocomputing. 463. 566–579. 20 indexed citations
7.
Camilleri, Kenneth P., Alfredo Ferreira, Johann Habakuk Israel, et al.. (2019). Sketch-based interaction and modeling: where do we stand?. Artificial intelligence for engineering design analysis and manufacturing. 33(4). 370–388. 27 indexed citations
8.
Padfield, Natasha, Jaime Zabalza, Huimin Zhao, Valentín Masero, & Jinchang Ren. (2019). EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges. Sensors. 19(6). 1423–1423. 376 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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