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Study on building subject-specific classifiers based on EEG data

In a modern human-machine system, it is very meaningful to study the subject-specific mental workload classification for the increasing high mental workload. In this paper, EEG data is used to build the Subject-specific Classifiers (SSCs) based on Stochastic Configuration Network (SCN). SCN has the advantage of random neural network, and can realize the hyper-parameters setting. The results show that the SSCs built in this paper perform well, the range of SSCs test accuracies is between 56.5% and 90.2% with an average of 75.9%.