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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/89636


    Title: 基於眼動的閱讀障礙分析與診斷;Analysis and Diagnosis of Dyslexia Based on Eye Movement
    Authors: 楊軒宇;Yang, Hsuan-Yu
    Contributors: 軟體工程研究所
    Keywords: 閱讀障礙;眼球運動;數據融合;虛擬現實;機器學習;Dyslexia;Eye movement;Data fusion;Virtual Reality;Machine learning
    Date: 2022-08-22
    Issue Date: 2022-10-04 11:50:18 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 閱讀障礙,是指在閱讀和寫作方面有困難,但沒有明顯的智力缺陷,也沒有
    相關的視覺或聽覺障礙的病症。症狀的嚴重程度因文化和個人因素而異。其他可
    能的症狀包括拼寫單詞困難,朗讀速度較慢,以及無法在頭腦中說出單詞。然而,
    要完全診斷出閱讀障礙是很困難的,因為當事人必須首先證明學習成績低下,而
    文化剝奪是導致成績低下的一種環境學習形式。
    因此,有必要提供一種快速有效的診斷輔助和學習幫助。隨著虛擬現實、眼
    動和機器學習的快速發展,我們建立了一個虛擬閱讀環境,並從收集到的眼動生
    理信息中計算出三個特徵集,包括眼動特徵、句子和視覺顯著圖。我們還提出了
    一個融合模型,整合了多個機器學習模型,通過評估相關數據來評估閱讀障礙,
    並利用從用戶反應中獲得的生理數據,建立一個基於真實數據的更客觀的自動評
    估模型。
    ;Dyslexia, or Reading Disorder, is a condition in which a person has difficulty reading and
    writing without significant intellectual deficits and without associated visual or auditory
    impairments. The severity of symptoms varies depending on cultural and personal factors.
    Other possible symptoms include difficulty spelling words, slower reading aloud, and inability
    to say words in the head. However, it is difficult to fully diagnose dyslexia because the person
    must first demonstrate low academic achievement, and cultural deprivation is a form of
    environmental learning that causes low achievement. Therefore, there is a need to provide a
    fast and effective diagnostic aid and learning aid. With the rapid development of virtual reality,
    eye-movement and machine learning, we build a virtual reading environment and compute
    three feature sets, including eye-movement features, word vectors and saliency maps, from
    the collected eye-movement physiological information. We also propose a fusion model that
    integrates several machine learning models to assess dyslexia by evaluating relevant data, and
    build a more objective automatic assessment model based on real data by using physiological
    data obtained from users′ responses are able to provide a more effective system in
    Methamphetamine treatment.
    Appears in Collections:[Software Engineer] Electronic Thesis & Dissertation

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