文本呈现方式对视觉舒适度的影响－基于人工智能与脑电协同的分析

Prior research has certified the value of implementing Artificial intelligence and brain neuroscience on revealing the law of education. There still lacks empirical research to clarify the technological path and interpretation method although some studies have theoretically elaborated the value of combining the two disciplines. The possible reason may due to the deficiency of intelligent feature extraction scheme of complex neural data and adaptive classification and prediction model. Based on EEG technique, the current study recruited 40 online German learners to read 60 German sentences presented in four media representations in online context. Based on the method of variational mode decomposition and sample entropy, the internal reasons for the influence of different digital resources on visual comfort were analyzed from different brain functional areas and bands of learners. Finally, the classification method of machine learning is used to compare the automatic recognition accuracy of visual comfort level