Javier Mínguez

5.7k total citations
97 papers, 3.3k citations indexed

About

Javier Mínguez is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition. According to data from OpenAlex, Javier Mínguez has authored 97 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Cognitive Neuroscience, 28 papers in Cellular and Molecular Neuroscience and 26 papers in Computer Vision and Pattern Recognition. Recurrent topics in Javier Mínguez's work include EEG and Brain-Computer Interfaces (51 papers), Neuroscience and Neural Engineering (28 papers) and Robotic Path Planning Algorithms (22 papers). Javier Mínguez is often cited by papers focused on EEG and Brain-Computer Interfaces (51 papers), Neuroscience and Neural Engineering (28 papers) and Robotic Path Planning Algorithms (22 papers). Javier Mínguez collaborates with scholars based in Spain, France and Switzerland. Javier Mínguez's co-authors include Luis Montano, Luis Montesano, Iñaki Iturrate, Javier M. Antelis, Andrea Kübler, Carlos Escolano, Eduardo López‐Larraz, Florent Lamiraux, Ángel Gil-Agudo and José del R. Millán and has published in prestigious journals such as PLoS ONE, Scientific Reports and IEEE Transactions on Biomedical Engineering.

In The Last Decade

Javier Mínguez

90 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Javier Mínguez Spain 32 1.9k 994 882 820 631 97 3.3k
Teodiano Bastos-Filho Brazil 30 1.5k 0.8× 668 0.7× 599 0.7× 198 0.2× 833 1.3× 283 3.3k
Luis Montesano Spain 30 1.4k 0.8× 736 0.7× 599 0.7× 397 0.5× 342 0.5× 87 2.9k
Marnix Nuttin Belgium 19 1.0k 0.5× 474 0.5× 598 0.7× 305 0.4× 632 1.0× 75 1.9k
Rafael Barea Spain 24 859 0.5× 607 0.6× 153 0.2× 331 0.4× 918 1.5× 109 2.6k
Yoky Matsuoka United States 28 971 0.5× 526 0.5× 247 0.3× 415 0.5× 220 0.3× 95 3.4k
Mansour Alsulaiman Saudi Arabia 34 1.5k 0.8× 922 0.9× 564 0.6× 120 0.1× 801 1.3× 100 4.5k
Zhaojie Ju United Kingdom 36 647 0.3× 1.5k 1.5× 192 0.2× 384 0.5× 960 1.5× 214 4.1k
Elena López Spain 21 783 0.4× 548 0.6× 120 0.1× 337 0.4× 881 1.4× 81 2.3k
Xinjun Sheng China 34 2.1k 1.1× 251 0.3× 1.3k 1.5× 132 0.2× 616 1.0× 218 3.9k
Xingang Zhao China 29 901 0.5× 253 0.3× 295 0.3× 144 0.2× 383 0.6× 212 3.0k

Countries citing papers authored by Javier Mínguez

Since Specialization
Citations

This map shows the geographic impact of Javier Mínguez'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 Javier Mínguez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Javier Mínguez more than expected).

Fields of papers citing papers by Javier Mínguez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Mínguez. 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 Javier Mínguez. The network helps show where Javier Mínguez may publish in the future.

Co-authorship network of co-authors of Javier Mínguez

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Mínguez. A scholar is included among the top collaborators of Javier Mínguez 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 Javier Mínguez. Javier Mínguez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Montero‐Marín, Jesús, et al.. (2017). Efficacy of Neurofeedback on the Increase of Mindfulness-Related Capacities in Healthy Individuals: a Controlled Trial. Mindfulness. 9(1). 303–311. 24 indexed citations
2.
Iturrate, Iñaki, et al.. (2015). Analysis and asynchronous detection of gradually unfolding errors during monitoring tasks. Journal of Neural Engineering. 12(5). 56001–56001. 26 indexed citations
3.
López‐Larraz, Eduardo, Luis Montesano, Ángel Gil-Agudo, & Javier Mínguez. (2014). Continuous decoding of movement intention of upper limb self-initiated analytic movements from pre-movement EEG correlates. Journal of NeuroEngineering and Rehabilitation. 11(1). 153–153. 100 indexed citations
4.
Escolano, Carlos, Mayte Navarro-Gil, Javier Garcı́a-Campayo, et al.. (2014). A controlled study on the cognitive effect of alpha neurofeedback training in patients with major depressive disorder. Frontiers in Behavioral Neuroscience. 8. 296–296. 51 indexed citations
5.
Escolano, Carlos, Mayte Navarro-Gil, Javier Garcı́a-Campayo, & Javier Mínguez. (2013). EEG-based upper-alpha neurofeedback for cognitive enhancement in major depressive disorder: A preliminary, uncontrolled study. PubMed. 2013. 6293–6296. 9 indexed citations
6.
Iturrate, Iñaki, Luis Montesano, & Javier Mínguez. (2013). Task-dependent signal variations in EEG error-related potentials for brain–computer interfaces. Journal of Neural Engineering. 10(2). 26024–26024. 51 indexed citations
7.
Antelis, Javier M., Luis Montesano, Ander Ramos‐Murguialday, Niels Birbaumer, & Javier Mínguez. (2013). On the Usage of Linear Regression Models to Reconstruct Limb Kinematics from Low Frequency EEG Signals. PLoS ONE. 8(4). e61976–e61976. 84 indexed citations
8.
Iturrate, Iñaki, et al.. (2013). Using frequency-domain features for the generalization of EEG error-related potentials among different tasks. PubMed. 2013. 5263–5266. 31 indexed citations
9.
Iturrate, Iñaki, Ricardo Chavarriaga, Luis Montesano, Javier Mínguez, & José del R. Millán. (2012). Latency correction of error potentials between different experiments reduces calibration time for single-trial classification. PubMed. 2012. 3288–3291. 39 indexed citations
10.
Antelis, Javier M. & Javier Mínguez. (2012). DYNAMO: Concurrent dynamic multi-model source localization method for EEG and/or MEG. Journal of Neuroscience Methods. 212(1). 28–42. 3 indexed citations
11.
López‐Larraz, Eduardo, et al.. (2011). EEG single-trial classification of visual, auditive and vibratory feedback potentials in Brain-Computer Interfaces. PubMed. 2011. 4231–4234. 13 indexed citations
12.
Escolano, Carlos, et al.. (2011). EEG-based upper alpha neurofeedback training improves working memory performance. PubMed. 2011. 2327–2330. 107 indexed citations
13.
Antelis, Javier M. & Javier Mínguez. (2010). DYNAMO: Dynamic multi-model source localization method for EEG and/or MEG. PubMed. 11. 5141–5144. 1 indexed citations
14.
Antelis, Javier M. & Javier Mínguez. (2009). Dynamic solution to the EEG source localization problem using kalman filters and particle filters. PubMed. 2009. 77–80. 11 indexed citations
15.
Ortiz, Alberto, et al.. (2009). ABUG: A fast Bug-derivative anytime path planner with provable suboptimality bounds. 1–8. 1 indexed citations
16.
Mínguez, Javier, et al.. (2006). Toward a Metric-Based Scan Matching Algorithm for Displacement Estimation in 3D Workspaces. International Conference on Robotics and Automation. 5 indexed citations
17.
Mínguez, Javier & Luis Montano. (2004). The ego-kinodynamic space: collision avoidance for any shape mobile robots with kinematic and dynamic constraints. 1. 637–643. 7 indexed citations
18.
Mínguez, Javier, et al.. (1999). Hasta qué punto es válido el estudio con pulsioximetría. Progresos de Obstetricia y Ginecología. 42(90). 9032–9043.
19.
Mínguez, Javier, et al.. (1994). Control integrado de plagas de tomate en las Vegas del Guadiana. Boletín de sanidad vegetal. Plagas. 20(1). 243–246. 2 indexed citations
20.
Mínguez, Javier, et al.. (1992). Noctuidae de las Vegas Bajas del Guadiana (Badajoz). Boletín de sanidad vegetal. Plagas. 18(3). 591–601. 1 indexed citations

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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