SILVA, L.Carlos E. Thomaz THOMAZ, C. E.2022-01-122022-01-122019-09-05SILVA, L.; THOMAZ, C. E. A Multivariate Correlation Assessment of Chess Proficiency Using Brain Signals. Proceedings - 15th Workshop of Computer Vision, WVC 2019, p. 10-15, sept. 2019.https://repositorio.fei.edu.br/handle/FEI/3710© 2019 IEEE.Chess game has attracted the interest of many academic works with several experiments carried out to address the differences in brain activation on proficients and non-proficients chess players. However, none of these works takes into account explicitly the cognitive patterns of the chess players to rank and classify them. In our work, we aim to present a cognitive model, using EEG and multivariate statistical methods, to assess chess volunteers and compare their performance to the traditional metric based on accuracy and response time. In total, 32 volunteers have participated in this study based on visual stimuli computationally generated. Our main results show that it is important not only to top rank the volunteers with high accuracy and low response time, but also understand how the main brain processes occur to a chess expert to achieve such top performance.Acesso RestritoArtigo de evento10.1109/WVC.2019.8876928ChessElectroencephalographyPattern Recognition