Daniela Mattos

29 total papers · 803 total citations
21 papers, 460 citations indexed

About

Daniela Mattos is a scholar working on Cognitive Neuroscience, Biomedical Engineering and Physical Therapy, Sports Therapy and Rehabilitation. According to data from OpenAlex, Daniela Mattos has authored 21 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Cognitive Neuroscience, 10 papers in Biomedical Engineering and 8 papers in Physical Therapy, Sports Therapy and Rehabilitation. Recurrent topics in Daniela Mattos's work include Motor Control and Adaptation (12 papers), Balance, Gait, and Falls Prevention (8 papers) and Muscle activation and electromyography studies (8 papers). Daniela Mattos is often cited by papers focused on Motor Control and Adaptation (12 papers), Balance, Gait, and Falls Prevention (8 papers) and Muscle activation and electromyography studies (8 papers). Daniela Mattos collaborates with scholars based in United States, Brazil and United Kingdom. Daniela Mattos's co-authors include Mark L. Latash, Vladimir M. Zatsiorsky, Satyajit Ambike, J. P. Scholz, Jonathan Ache Dias, Gregor Schöner, John P. Scholz, Márcio Fagundes Goethel, Daniela Virgínia Vaz and Hang Jin Jo and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Journal of Neurophysiology.

In The Last Decade

Daniela Mattos

21 papers receiving 447 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Daniela Mattos	357	303	144	105	57	21	460
K. M. Newell	269 0.8×	148 0.5×	144 1.0×	76 0.7×	76 1.3×	13	434
Firas Mawase	326 0.9×	204 0.7×	103 0.7×	84 0.8×	19 0.3×	25	476
Violaine Cahouët	196 0.5×	128 0.4×	93 0.6×	74 0.7×	42 0.7×	13	438
Halla Olafsdottir	480 1.3×	382 1.3×	153 1.1×	127 1.2×	13 0.2×	11	550
Chantal Bard	303 0.8×	139 0.5×	123 0.9×	75 0.7×	38 0.7×	10	485
Nancy St-Onge	164 0.5×	270 0.9×	126 0.9×	39 0.4×	97 1.7×	19	488
M. Bonnard	217 0.6×	227 0.7×	117 0.8×	26 0.2×	94 1.6×	15	474
A. Boyadjian	192 0.5×	143 0.5×	144 1.0×	37 0.4×	130 2.3×	12	432
Young Uk Ryu	240 0.7×	109 0.4×	105 0.7×	135 1.3×	55 1.0×	40	451
Katherine M. Deutsch	266 0.7×	191 0.6×	57 0.4×	68 0.6×	59 1.0×	18	445

Countries citing papers authored by Daniela Mattos

Since Specialization

Citations

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

Fields of papers citing papers by Daniela Mattos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniela Mattos

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

All Works

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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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