A study on the analysis of auditory cortex active status by music genre: Drawing on EEG
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, S.-M. | - |
dc.contributor.author | Sim, K.-B. | - |
dc.date.accessioned | 2021-09-16T06:40:53Z | - |
dc.date.available | 2021-09-16T06:40:53Z | - |
dc.date.issued | 2011 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/49254 | - |
dc.description.abstract | Music is the pattern of sounds produced by people singing of playing instruments. Thus, the music is made by people. Music composer, will be planted in the human emotions, put the listener is able to feel a similar sentiment. Especially, interesting from our point of view is that music analysis, the emotions of the people can be analyzed. This paper focuses on the analysis of auditory cortex active status by music genre. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP(Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG. In addition, drawing on LORETA(Low Resolution Brain Electromagnetic Tomography)program have attempt to design location of electrode in brain. And finally, using EEGLAB, the relationship of music and the auditory cortex active status could be concluded. © 2011 IEEE. | - |
dc.format.extent | 4 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | A study on the analysis of auditory cortex active status by music genre: Drawing on EEG | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/FSKD.2011.6019916 | - |
dc.identifier.bibliographicCitation | Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, v.3, pp 1916 - 1919 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-80053414825 | - |
dc.citation.endPage | 1919 | - |
dc.citation.startPage | 1916 | - |
dc.citation.title | Proceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011 | - |
dc.citation.volume | 3 | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | Brain-Computer Interface | - |
dc.subject.keywordAuthor | EEG | - |
dc.subject.keywordAuthor | Music Genre Distinction | - |
dc.subject.keywordAuthor | Pattern Recognition | - |
dc.subject.keywordAuthor | Variance-Considered Machine | - |
dc.subject.keywordPlus | Auditory cortex | - |
dc.subject.keywordPlus | Averaging method | - |
dc.subject.keywordPlus | EEG signals | - |
dc.subject.keywordPlus | Event related potentials | - |
dc.subject.keywordPlus | Human emotion | - |
dc.subject.keywordPlus | ICA algorithms | - |
dc.subject.keywordPlus | Low resolution brain electromagnetic tomographies | - |
dc.subject.keywordPlus | Music analysis | - |
dc.subject.keywordPlus | Music composers | - |
dc.subject.keywordPlus | Music genre | - |
dc.subject.keywordPlus | Noise removal | - |
dc.subject.keywordPlus | Variance-Considered Machine | - |
dc.subject.keywordPlus | Fuzzy systems | - |
dc.subject.keywordPlus | Pattern recognition | - |
dc.subject.keywordPlus | Interfaces (computer) | - |
dc.description.journalRegisteredClass | scopus | - |
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