Exploration of User's Mental State Changes during Performing Brain-Computer Interface. Sensors (Basel) 2020 Jun 03;20(11)
Date
06/07/2020Pubmed ID
32503162Pubmed Central ID
PMC7308896DOI
10.3390/s20113169Scopus ID
2-s2.0-85086008478 (requires institutional sign-in at Scopus site) 27 CitationsAbstract
Substantial developments have been established in the past few years for enhancing the performance of brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). The past SSVEP-BCI studies utilized different target frequencies with flashing stimuli in many different applications. However, it is not easy to recognize user's mental state changes when performing the SSVEP-BCI task. What we could observe was the increasing EEG power of the target frequency from the user's visual area. BCI user's cognitive state changes, especially in mental focus state or lost-in-thought state, will affect the BCI performance in sustained usage of SSVEP. Therefore, how to differentiate BCI users' physiological state through exploring their neural activities changes while performing SSVEP is a key technology for enhancing the BCI performance. In this study, we designed a new BCI experiment which combined working memory task into the flashing targets of SSVEP task using 12 Hz or 30 Hz frequencies. Through exploring the EEG activity changes corresponding to the working memory and SSVEP task performance, we can recognize if the user's cognitive state is in mental focus or lost-in-thought. Experiment results show that the delta (1-4 Hz), theta (4-7 Hz), and beta (13-30 Hz) EEG activities increased more in mental focus than in lost-in-thought state at the frontal lobe. In addition, the powers of the delta (1-4 Hz), alpha (8-12 Hz), and beta (13-30 Hz) bands increased more in mental focus in comparison with the lost-in-thought state at the occipital lobe. In addition, the average classification performance across subjects for the KNN and the Bayesian network classifiers were observed as 77% to 80%. These results show how mental state changes affect the performance of BCI users. In this work, we developed a new scenario to recognize the user's cognitive state during performing BCI tasks. These findings can be used as the novel neural markers in future BCI developments.
Author List
Ko LW, Chikara RK, Lee YC, Lin WCAuthor
Rupesh Chikara PhD Postdoctoral Fellow in the Neurology department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
AdolescentAdult
Bayes Theorem
Brain-Computer Interfaces
Cognition
Electroencephalography
Evoked Potentials, Visual
Female
Humans
Male
Memory, Short-Term
Photic Stimulation
Young Adult
