Analysis of instantaneous brain interactions contribution to a motor imagery classification task - Cristancho Cuervo, Jorge Humberto; Delgado Saa, Jaime F.; Ripoll Solano, Lácides Antonio (Frontiers in Computational Neuroscience, 2022)
The purpose of the study is analyze the contribution of interactions between electrodes, measured here as correlation or Jaccard distance, to the classification of two actions in a motor imagery paradigm: left-hand or right-hand movement. The analysis is performed in two classifier models: a static (linear discriminant analysis) and a dynamic (hidden conditional random field) model. The impact of using the sliding window technique (SWT) in the static and dynamic models is also analyzed here. The study proved that their combination with temporal features provides important information to improve the classification in a two-class motor imagery task. Also, we showed that adding interactions between electrodes significantly improves the performance of each classifier, regarding the nature of the interaction measure.