Eric Laciar

1.9k total citations
61 papers, 1.3k citations indexed

About

Eric Laciar is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Biomedical Engineering. According to data from OpenAlex, Eric Laciar has authored 61 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cardiology and Cardiovascular Medicine, 29 papers in Cognitive Neuroscience and 18 papers in Biomedical Engineering. Recurrent topics in Eric Laciar's work include ECG Monitoring and Analysis (32 papers), EEG and Brain-Computer Interfaces (29 papers) and Cardiac electrophysiology and arrhythmias (19 papers). Eric Laciar is often cited by papers focused on ECG Monitoring and Analysis (32 papers), EEG and Brain-Computer Interfaces (29 papers) and Cardiac electrophysiology and arrhythmias (19 papers). Eric Laciar collaborates with scholars based in Argentina, Spain and United States. Eric Laciar's co-authors include Agustina Garcés Correa, Pablo Díez, Lorena Orosco, Vicente Mut, Max E. Valentinuzzi, R. Jané, Enrique Ávila‍, H. Daniel Patiño, Abel Torres and Pedro David Arini and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering and Computers in Biology and Medicine.

In The Last Decade

Eric Laciar

57 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Laciar Argentina 18 996 381 309 289 228 61 1.3k
M. Ramasubba Reddy India 16 572 0.6× 230 0.6× 251 0.8× 205 0.7× 78 0.3× 105 1.1k
Theerawit Wilaiprasitporn Thailand 16 740 0.7× 143 0.4× 167 0.5× 179 0.6× 178 0.8× 56 1.1k
Yongtian He United States 12 1.3k 1.3× 199 0.5× 184 0.6× 379 1.3× 148 0.6× 16 1.8k
Bernard Grundlehner Netherlands 17 702 0.7× 354 0.9× 92 0.3× 308 1.1× 251 1.1× 29 1.3k
Mehmet Akın Türkiye 14 710 0.7× 253 0.7× 271 0.9× 71 0.2× 255 1.1× 25 1.1k
Valentin Goverdovsky United Kingdom 15 514 0.5× 284 0.7× 102 0.3× 107 0.4× 118 0.5× 24 968
M. Kemal Kıymık Türkiye 13 645 0.6× 201 0.5× 325 1.1× 111 0.4× 81 0.4× 23 1.0k
Alexander Craik United States 5 894 0.9× 169 0.4× 156 0.5× 186 0.6× 136 0.6× 9 1.0k
Min-Ho Lee South Korea 15 1.2k 1.2× 101 0.3× 187 0.6× 485 1.7× 116 0.5× 55 1.5k
Pasin Israsena Thailand 15 777 0.8× 152 0.4× 154 0.5× 79 0.3× 426 1.9× 45 1.0k

Countries citing papers authored by Eric Laciar

Since Specialization
Citations

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

Fields of papers citing papers by Eric Laciar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Laciar

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Laciar. A scholar is included among the top collaborators of Eric Laciar 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 Eric Laciar. Eric Laciar 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.
2.
Correa, R., et al.. (2017). Quaternion Neural Network with Temporal Feedback Calculation: Application to Cardiac Vector Velocity during Myocardial Infarction. Conicet. 1 indexed citations
3.
Correa, Agustina Garcés, Lorena Orosco, Pablo Díez, & Eric Laciar. (2014). Automatic detection of epileptic seizures in long-term EEG records. Computers in Biology and Medicine. 57. 66–73. 31 indexed citations
4.
Díez, Pablo, et al.. (2013). FEATURES EXTRACTION METHOD FOR BRAIN-MACHINE COMMUNICATION BASED ON THE EMPIRICAL MODE DECOMPOSITION. Biomedical Engineering Applications Basis and Communications. 25(6). 1350058. 3 indexed citations
5.
Díez, Pablo, et al.. (2013). FEATURES EXTRACTION METHOD FOR BRAIN-MACHINE COMMUNICATION BASED ON THE EMPIRICAL MODE DECOMPOSITION. Biomedical Engineering Applications Basis and Communications. 25(6). 1350058–1350058. 4 indexed citations
6.
Arini, Pedro David, et al.. (2012). Study of QRS-loop parameters and conventional ST-T indexes for identification of ischemic and healthy subjects. Computing in Cardiology. 649–652. 3 indexed citations
7.
Müller, Sandra, Pablo Díez, Teodiano Bastos-Filho, et al.. (2011). SSVEP-BCI implementation for 37–40 Hz frequency range. PubMed. 2011. 6352–6355. 21 indexed citations
8.
Laciar, Eric, et al.. (2010). Analysis of QRS loop in the Vectorcardiogram of patients with Chagas' disease. PubMed. 33. 2561–2564. 11 indexed citations
9.
Orosco, Lorena, Agustina Garcés Correa, & Eric Laciar. (2010). Multiparametric detection of epileptic seizures using Empirical Mode Decomposition of EEG records. PubMed. 2010. 951–954. 23 indexed citations
10.
Orosco, Lorena & Eric Laciar. (2009). Analysis of ventricular late potentials in high resolution ecg records by time-frequency representations. Latin American Applied Research - An international journal. 39(3). 255–260. 8 indexed citations
11.
Orosco, Lori, et al.. (2009). An epileptic seizures detection algorithm based on the empirical mode decomposition of EEG. 2651–2654. 37 indexed citations
12.
Díez, Pablo, Vicente Mut, Eric Laciar, Abel Torres, & Enrique Ávila‍. (2009). Application of the empirical mode decomposition to the extraction of features from EEG signals for mental task classification. PubMed. 2009. 2579–2582. 45 indexed citations
13.
Arini, Pedro David & Eric Laciar. (2009). Quantification of Cardiac Ventricular Repolarization and its Spatial Dispersion through the Surface Electrocardiogram. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 1 indexed citations
14.
Correa, R., Eric Laciar, Pedro David Arini, & R. Jané. (2009). Analysis of QRS loop changes in the beat-to-beat Vectocardiogram of ischemic patients undergoing PTCA. PubMed. 2009. 1750–1753. 10 indexed citations
15.
Laciar, Eric, et al.. (2009). Sleep apnea detection based on spectral analysis of three ECG - derived respiratory signals. PubMed. 2009. 4723–4726. 25 indexed citations
16.
Laciar, Eric, et al.. (2008). Performance evaluation of three methods for respiratory signal estimation from the electrocardiogram. PubMed. 2008. 4760–4763. 15 indexed citations
17.
Díez, Pablo, Eric Laciar, Vicente Mut, Enrique Ávila‍, & Abel Torres. (2008). A comparative study of the performance of different spectral estimation methods for classification of mental tasks. PubMed. 2008. 1155–1158. 16 indexed citations
18.
Laciar, Eric, R. Jané, & Dana H. Brooks. (2006). Evaluation of myocardial damage in chagasic patients from the signal-averaged and beat-to beat analysis of the high resolution electrocardiogram. Computing in Cardiology Conference. 25–28. 7 indexed citations
19.
Laciar, Eric & R. Jané. (2005). Detección y Análisis Latido a Latido de Potenciales Tardíos Ventriculares mediante mapas Espectro-Temporales. Revista Iberoamericana de Automática e Informática Industrial RIAI. 2(3). 74–82.
20.
Laciar, Eric & R. Jané. (2002). An improved weighted signal averaging method for high-resolution ECG signals. 69–72. 13 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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