Javier Navallas

405 total citations
53 papers, 257 citations indexed

About

Javier Navallas is a scholar working on Biomedical Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Javier Navallas has authored 53 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Biomedical Engineering, 21 papers in Cognitive Neuroscience and 16 papers in Cellular and Molecular Neuroscience. Recurrent topics in Javier Navallas's work include Muscle activation and electromyography studies (46 papers), Neuroscience and Neural Engineering (16 papers) and Advanced Sensor and Energy Harvesting Materials (14 papers). Javier Navallas is often cited by papers focused on Muscle activation and electromyography studies (46 papers), Neuroscience and Neural Engineering (16 papers) and Advanced Sensor and Energy Harvesting Materials (14 papers). Javier Navallas collaborates with scholars based in Spain, Bulgaria and Denmark. Javier Navallas's co-authors include Armando Malanda, Javier Rodríguez-Falces, Ignacio Rodríguez, Javier Rodríguez, Arantxa Villanueva, Rafael Cabeza, Juan Luis Alcázar, Alayn Loayssa, Mikel Sagues and N.A. Dimitrova and has published in prestigious journals such as Sensors, Clinical Neurophysiology and European Journal of Applied Physiology.

In The Last Decade

Javier Navallas

49 papers receiving 254 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 Navallas Spain 9 171 78 61 31 22 53 257
Muhammad Zia ur Rehman Pakistan 10 270 1.6× 176 2.3× 82 1.3× 160 5.2× 4 0.2× 22 520
Dianning He China 10 52 0.3× 103 1.3× 42 0.7× 146 4.7× 6 0.3× 32 341
Sami Arıca Türkiye 9 48 0.3× 265 3.4× 126 2.1× 28 0.9× 6 0.3× 27 337
Radim Krupička Czechia 11 149 0.9× 46 0.6× 37 0.6× 21 0.7× 46 421
I‐Chieh Lee United States 10 116 0.7× 56 0.7× 19 0.3× 17 0.5× 1 0.0× 27 292
John McLinden United States 9 69 0.4× 178 2.3× 64 1.0× 57 1.8× 28 265
Yuxi Luo China 13 90 0.5× 206 2.6× 12 0.2× 7 0.2× 8 0.4× 60 493
Q.H. Huang Hong Kong 4 273 1.6× 57 0.7× 49 0.8× 80 2.6× 6 359
Nicole Shuang Yu Chia Singapore 13 93 0.5× 35 0.4× 66 1.1× 39 1.3× 24 455
G. Venugopal India 11 296 1.7× 106 1.4× 35 0.6× 9 0.3× 48 462

Countries citing papers authored by Javier Navallas

Since Specialization
Citations

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

Fields of papers citing papers by Javier Navallas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Javier Navallas

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Navallas. A scholar is included among the top collaborators of Javier Navallas 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 Navallas. Javier Navallas 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.
Fernández‐Seara, María A., Paloma Leticia Martín-Moreno, Nuria Garcı́a-Fernández, et al.. (2025). Advancing ASL kidney image registration: a tailored pipeline with VoxelMorph. Neural Computing and Applications. 37(14). 8347–8369. 1 indexed citations
2.
Navallas, Javier, et al.. (2025). The Probability Density Function (PDF) of surface EMG with increasing force: a comparison between the tibialis anterior and the vastus lateralis. Journal of Electromyography and Kinesiology. 84. 103029–103029.
3.
Navallas, Javier, et al.. (2025). EMG filling analysis, a new method for the assessment of recruitment of motor units with needle EMG. Neurophysiologie Clinique. 55(4). 103059–103059.
4.
Rodríguez-Falces, Javier, et al.. (2024). The probability density function of the surface electromyogram and its dependence on contraction force in the vastus lateralis. BioMedical Engineering OnLine. 23(1). 1 indexed citations
5.
Rodríguez-Falces, Javier, et al.. (2024). The filling factor of the sEMG signal at low contraction forces in the quadriceps muscles is influenced by the thickness of the subcutaneous layer. Frontiers in Physiology. 14. 1298317–1298317. 4 indexed citations
6.
7.
Fernández‐Seara, María A., Paloma Leticia Martín-Moreno, Nuria Garcı́a-Fernández, et al.. (2023). A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI. Magnetic Resonance Imaging. 104. 39–51. 2 indexed citations
8.
Malanda, Armando, et al.. (2022). Automatic jitter measurement in needle-detected motor unit potential trains. Computers in Biology and Medicine. 149. 105973–105973. 1 indexed citations
9.
Rodríguez-Falces, Javier, Armando Malanda, & Javier Navallas. (2021). Effects of muscle shortening on single-fiber, motor unit, and compound muscle action potentials. Medical & Biological Engineering & Computing. 60(2). 349–364. 7 indexed citations
10.
Rodríguez-Falces, Javier, et al.. (2019). Recovery of the first and second phases of the M wave after prolonged maximal voluntary contractions. Journal of Electromyography and Kinesiology. 50. 102385–102385. 1 indexed citations
11.
Malanda, Armando, et al.. (2018). A masked least-squares smoothing procedure for artifact reduction in scanning-EMG recordings. Medical & Biological Engineering & Computing. 56(8). 1391–1402. 1 indexed citations
12.
Rodríguez-Falces, Javier, et al.. (2016). Influence of timing variability between motor unit potentials on M-wave characteristics. Journal of Electromyography and Kinesiology. 30. 249–262. 4 indexed citations
13.
Cabeza, Rafael, et al.. (2015). Ultrasound Image Discrimination between Benign and Malignant Adnexal Masses Based on a Neural Network Approach. Ultrasound in Medicine & Biology. 42(3). 742–752. 35 indexed citations
14.
Malanda, Armando, et al.. (2015). Averaging methods for extracting representative waveforms from motor unit action potential trains. Journal of Electromyography and Kinesiology. 25(4). 581–595. 9 indexed citations
15.
Rodríguez-Falces, Javier, et al.. (2012). Influence of the shape of intracellular potentials on the morphology of single-fiber extracellular potentials in human muscle fibers. Medical & Biological Engineering & Computing. 50(5). 447–460. 8 indexed citations
16.
Rodríguez, Javier, et al.. (2010). Analysis of the relationship between the rise-time and the amplitude of single-fibre potentials in human muscles. Journal of Electromyography and Kinesiology. 20(6). 1249–1258. 1 indexed citations
17.
Rodríguez, Javier, Javier Navallas, & Armando Malanda. (2010). Teaching a master student how to model the electrical potentials produced by the muscle. International journal of engineering education. 26(6). 1391–1404. 2 indexed citations
18.
Rodríguez, Javier, et al.. (2009). Relationship between the rise-time of single-fibre action potentials and radial distance in human muscle fibres. Clinical Neurophysiology. 121(2). 214–220. 4 indexed citations
19.
Navallas, Javier, et al.. (2008). Mathematical analysis of a muscle architecture model. Mathematical Biosciences. 217(1). 64–76. 7 indexed citations
20.
Rodríguez, Ignacio, Armando Malanda, Fermín Mallor, et al.. (2007). Motor Unit Action Potential Duration, II: A New Automatic Measurement Method Based on the Wavelet Transform. Journal of Clinical Neurophysiology. 24(1). 59–69. 6 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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