Recognition of high ruminant population based on natural language and EEG
Journal Title: Journal of Air Force Medical University - Year 2023, Vol 44, Issue 10
Abstract
Objective To investigate a new model that can be used to identify people with high rumination through the electroencephalogram (EEG) signal features induced by natural language, based on EEG technology. Methods A total of 46 people with high rumination ( ruminant group) and 29 normal subjects ( control group) were analyzed, the self-developed stimulus corpus was used as the inducing material for rumination, the EEG signals were collected when subjects were reading stimulus materials and answering questions, the signal coherence characteristics between different channel pairs were calculated, and a classification and recognition model of high ruminant population was constructed by support vector machine. Results The support vector machine classification study showed that the accuracy of using only neutral questions and ruminant questions to classify the ruminant population was 86. 67% and 66. 67% , respectively, while the accuracy of using the coherence characteristics of the whole brain EEG signals of the two kinds of stimulus materials for classification was 86. 67% , and it had good sensitivity and specificity. Conclusion The above results show that the rumination scale combined with EEG technology based on natural language analysis can assist in identifying people with high rumination to a certain extent, which can be used as a new paradigm for exploring psychometrics.
Authors and Affiliations
LI Chenxi, LI Yulong, WANG Lingling, LIN Xinxin, DAI Hong, CUI Di, FANG Peng, MIAO Danmin
Keywords
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