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%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2021/09.03.01.16
%2 sid.inpe.br/sibgrapi/2021/09.03.01.16.33
%@doi 10.1109/SIBGRAPI54419.2021.00050
%T Performance analysis of chess players comparing traditional and novel cognitive perception ranking measures
%D 2021
%A Silva Junior, Laercio,
%A Silva, Wilson da,
%A Thomaz, Carlos,
%@affiliation Centro Universitário FEI 
%@affiliation Centro Universitário UniDomBosco 
%@affiliation Centro Universitário FEI
%E Paiva, Afonso ,
%E Menotti, David ,
%E Baranoski, Gladimir V. G. ,
%E Proença, Hugo Pedro ,
%E Junior, Antonio Lopes Apolinario ,
%E Papa, João Paulo ,
%E Pagliosa, Paulo ,
%E dos Santos, Thiago Oliveira ,
%E e Sá, Asla Medeiros ,
%E da Silveira, Thiago Lopes Trugillo ,
%E Brazil, Emilio Vital ,
%E Ponti, Moacir A. ,
%E Fernandes, Leandro A. F. ,
%E Avila, Sandra,
%B Conference on Graphics, Patterns and Images, 34 (SIBGRAPI)
%C Gramado, RS, Brazil (virtual)
%8 18-22 Oct. 2021
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Chess, EEG, Eye-tracking, Pattern recognition.
%X Traditionally, proficiency in chess has been measured by metrics based on accuracy and response time or performance in tournaments, but not considering how cognitive signals influence in the decision making in this complex game. In this work, we have carried out a performance analysis of chess players comparing a standard ranking measure with a novel one proposed here. Using the idea of treating participants eye movements and brain signals, when answering several on-screen valid chess questions of distinguished complexities, as high-dimensional data we have shown that expertise is consistently associated with the ability to process visual information holistically using fewer fixations rather than locally focusing on individual pieces. Results show that traditional metric to quantify proficiency presented accuracy up to 73,3\%, while the proposed cognitive one reached accuracy up to 87,5\% and 98,9\% for the electroencephalography and eye movements, respectively. These findings might disclose new insights for teaching and predicting chess skills.
%@language en
%3 61-camera_ready.pdf


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