博碩士論文 109521093 完整後設資料紀錄

DC 欄位 語言
DC.contributor電機工程學系zh_TW
DC.creator董凱仁zh_TW
DC.creatorKai-Jen Tungen_US
dc.date.accessioned2022-7-28T07:39:07Z
dc.date.available2022-7-28T07:39:07Z
dc.date.issued2022
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=109521093
dc.contributor.department電機工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本論文基於共空間模式(Common Spatial Patterns, CSP)與黎曼流形(Riemannian Manifold)切線空間映射(Tangent Space Mapping, TSM),用於腦電訊號(Electroencephalography, EEG)多分類任務上。藉由濾波器組(Filter Bank)與共變異數矩陣(Covariance Matrix)計算出各個通道間的頻譜功率,再用共空間模式與黎曼流形的切線空間映射分別提取特徵,最後透過基於支持向量機(Support Vector Machine, SVM)的新型分類器分類。資料集使用BCI competition IV 2a想像運動(Motor Imagery, MI)四分類準確率達到78.55%,BCI competition III 3a想像運動四分類準確率達到83.33%,自行錄製之想像運動四分類準確率達到57.44%,自行錄製之實際運動四分類準確率達到81.25%。zh_TW
dc.description.abstractThis paper is based on common spatial patterns (CSP) and Riemannian Manifold tangent space mapping (TSM) for Electroencephalography (EEG) of multiclass classification tasks. The spectral power between each channel is calculated by the filter bank and the covariance matrix, and then the features are extracted by the CSP and TSM respectively, and finally the new classifier based on Support Vector Machine (SVM) is used to classify. The datasets used BCI competition IV 2a motor imagery (MI) four-classes accuracy rate achieved 78.55%, BCI competition III 3a MI four-classes accuracy rate achieved 83.33%, self-recorded MI four-classes accuracy rate achieved 57.44%, self-recorded motor movement four-classes accuracy rate achieved 81.25%.en_US
DC.subject腦電圖zh_TW
DC.subject腦機介面zh_TW
DC.subject想像運動zh_TW
DC.subject多分類zh_TW
DC.subject共空間模式zh_TW
DC.subject黎曼流形切線空間zh_TW
DC.subjectEEGen_US
DC.subjectbrain-computer interfaceen_US
DC.subjectmotor imageryen_US
DC.subjectmulticlass class-ificationen_US
DC.subjectcommon spatial patternsen_US
DC.subjectRiemann tangent spaceen_US
DC.title基於共空間模式與黎曼流形之即時腦波多分類zh_TW
dc.language.isozh-TWzh-TW
DC.titleCommon Spatial Patterns and Riemannian Manifold based Real-Time Classification of Multiclass EEGen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明