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Study On EEG Feature Of Different Emotional States

Posted on:2015-02-21Degree:MasterType:Thesis
Country:ChinaCandidate:X T WangFull Text:PDF
GTID:2268330425993813Subject:Biomedical engineering
Abstract/Summary:PDF Full Text Request
With the development of economy, people’s demand of living standard become more and more increasingly, bringing a lot of pressure invisibly, leading to a variety of neurological diseases eventually, such as endocrine disorders caused by the pressure, depression, psychosis, etc. Then affecting the patients’mood and behavior, and bringing great distress to their daily lives. There are studies have shown that children with autism, ADHD, growth retardation on languages and others also can show a certain emotional and behavioral problems. Therefore, the study on emotional perception can make for the treatment of these diseases.The brain is one of the most delicate and complex organs, containing a wealth of information about physiology and pathology, so the research proposes a study on emotional perception based on electroencephalograph (EEG), to explore the changes of EEG with the factors by analyzing the characteristics’differences of EEG in different emotional states.Firstly, picking out outgoing and stable persons as the subjects according to the Eysenck Personality Questionnaire, the EEGs of subjects with eyes closed in a quiet state as the references, choosing different types of pure music as stimulus to induce different kinds of emotion, At the same time acquiring EEGs and EOG signals. Then, denoising for EEGs and separating EOG artifacts. Finally, extracting EEG signals’amplitude histogram in time domain, power spectral density in frequency domain, Hilbert spectrum entropy in time-frequency domain respectively. Then analysis EEGs’changes qualitatively and quantitatively. The research not only analysis EEG signals’and their four basic rhythms’ changes integrated the four factors of gender, age, region of the brain, emotion for the first time, and the Hilbert spectrum entropy was first used for time-frequency analysis of EEG signals, it will be a new classified index for emotion recognition. These results not only reveal the brain mechanism in different emotional states, but also provide theoretical basis for emotional perception, music therapy and neuroscience.
Keywords/Search Tags:emotion, electroencephalograph(EEG), music, feature extractionHilbert spectral entropy
PDF Full Text Request
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