Abstract
Mind Wandering (MW) is the repetitive event where our mind focuses on our internal thoughts rather than the task in our hand. MW can have both good as well as detrimental effects. Hence, it is crucial to measure MW. This interesting phenomenon and part of our daily life can be effectively measured using EEG signals. Several techniques that have been used to predict MW. However, literature shows that there are still chances of further improvement in this field. Therefore, in this paper we proposed a framework based on data mining and machine learning to detect MW using EEG signals. In our framework, we extracted a number of features EEG channels. The performance of our proposed framework has been evaluated using 19 sessions of two subjects. The accuracy of the proposed framework is higher than the other researches under this field that indicates the superiority of our proposed framework.
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