Tracey Cassar

12 papers receiving 842 citations

Hit Papers

Review on solving the inverse problem in EEG source analysis20082026201420202008250500750

Peers

Tracey Cassar
Comparison fields: 5 of 90
  • Cognitive Neuroscience 666
  • Signal Processing 149
  • Radiology, Nuclear Medicine and Imaging 106
  • Cellular and Molecular Neuroscience 83
  • Biomedical Engineering 63
Replace Joseph Muscat with:
Joseph Muscat Malta
Pavan Ramkumar United States
Mainak Jas United States
Sylvain Takerkart France
Ahmet Ademoğlu Türkiye
Alexandre Andrade Portugal
Jiri Vrba Germany
Zeynep Akalin Acar United States
Martin Luessi United States
Emmanuel Olivi France
Tracey Cassar relative to Joseph Muscat Malta Joseph Muscat's profile →
Citations per field
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Joseph Muscat · 1×
Citations per year

Countries citing papers authored by Tracey Cassar

Since Specialization
Citations

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

Fields of papers citing papers by Tracey Cassar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tracey Cassar

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

All Works

12 of 12 papers shown
#WorkIndexed citations
1 5
2 6
3 1
4 24
5 3
6
Review on solving the inverse problem in EEG source analysisbreakdown →
779
7 2
8 19
9
Applying ICA to Single Trial Auditory P300 and CNV Evoked Potentials to Provide Biomarkers
1
10
Comparison of Single Trial Back Projected Independent Components with the Averaged Waveform for the Extraction of Biomarkers of Auditory P300 Evoked Potentials
1
11 18
12
Validation of time-frequency and ARMA feature extraction methods in classification of mild epileptic signal patterns
1

About Tracey Cassar

Tracey Cassar is a scholar working on Signal Processing, Cognitive Neuroscience and Electrochemistry, having authored 12 papers that have together received 860 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (8 papers), Blind Source Separation Techniques (7 papers) and Functional Brain Connectivity Studies (3 papers). The work is most often cited by research in Cognitive Neuroscience (666 citations), Signal Processing (149 citations) and Computational Mathematics (3 citations). Tracey Cassar has collaborated with scholars based in Malta, Greece and Romania. Frequent co-authors include Simon G. Fabri, Tracey Camilleri, Michalis Zervakis, Vangelis Sakkalis, Joseph Muscat, Petros Xanthopoulos, Bart Vanrumste, Kenneth P. Camilleri, Sifis Micheloyannis and B.W. Jervis. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, Journal of NeuroEngineering and Rehabilitation and Physiological Measurement.

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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