博碩士論文 106522603 完整後設資料紀錄

DC 欄位 語言
DC.contributor資訊工程學系zh_TW
DC.creator潘思言zh_TW
DC.creatorSetyan Pamungkasen_US
dc.date.accessioned2019-7-17T07:39:07Z
dc.date.available2019-7-17T07:39:07Z
dc.date.issued2019
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=106522603
dc.contributor.department資訊工程學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract一般情況下,汽車駕駛人應使用雙手控制方向盤,否則將被視為不安全的駕駛行為。基於Aditya的論文,基於Aditya的論文,我們可以通過使用empirical mode decomposition (EMD)以及 Hilbert-Huang transform (HHT)從手錶的加速度計信號中萃取振動信息來檢測這些不安全的駕駛行為。 我們提出了一種新的方法來提高單手與雙手轉向操縱位置檢測,即為透過改用RBF-SVM和individual model和grouping model的建模方法。 我們的實驗結果顯示,通用模型中雙手檢測的準確率從75%提高到89%, individual model準確率為97%, grouping model準確率為93%。zh_TW
dc.description.abstractNormally when driving the car, the driver should hold the steering wheel with both hands. Otherwise, the action is considered as an unsafe behavior. Based on Aditya’s thesis, potentially we are able to detect those unsafe behaviors by extracting vibration information from watch’s accelerometer signal using empirical mode decomposition (EMD) and Hilbert-Huang transform (HHT). We propose new approach to improve the accuracy value of one hand versus two hand steering handling position detection by changing the classifier using SVM with RBF kernel and modeling approach using individual model and grouping model. Our experiment result shows that the accuracy is increasing from 75% to 89% for two hand detection in universal model, 97% average in individual model, and 93% average in grouping model.en_US
DC.subject分心駕駛檢測zh_TW
DC.subject駕駛人在方向盤的擺放位置zh_TW
DC.subject智慧手錶zh_TW
DC.subject經驗模態分解zh_TW
DC.subject希爾伯特-黃轉換zh_TW
DC.subjectdistracted driving detectionen_US
DC.subjectdriver’s hand positionen_US
DC.subjectsmartwatchen_US
DC.subjectempirical mode decompositionen_US
DC.subjectHilbert-Huang transform.en_US
DC.title以穿戴單一智慧型手錶利用多種建模策略偵測操縱方向盤之手部位置zh_TW
dc.language.isozh-TWzh-TW
DC.titleOn Several Modeling Approach for Detecting Steering Handling Position Using One Smartwatchen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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