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姓名 林鈺庭(Yu-Ting Lin) 查詢紙本館藏 畢業系所 電機工程學系 論文名稱 可選字及可再訓練眼寫系統
(Selectable and retrainable eye writing system)相關論文 檔案 [Endnote RIS 格式]
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摘要(中) 患有肌萎縮側索硬化症 (Amyotrophic lateral sclerosis, ALS)的病人，由
於運動神經元的退化，肌肉會逐漸萎縮，失去運動能力，無法利用口說和肢
體對外溝通，較晚開始退化的眼球運動功能成為後期病人希望可以依靠來
對外溝通的一個途徑。
本研究以阿拉伯數字(0~9)、大寫英文字母(A~Z)以及 4 個特殊符號(空
格、輸入、句點、問號)，共 40 個符號，建立一套眼寫系統。使用眼電圖法
（Electrooculography, EOG）記錄眼球運動，將 EOG 訊號轉為影像利用卷積
神經網路(Convolutional Neural Networks，CNN）進行符號辨識，以眨眼數
次當作特殊指令來控制進出書寫辨識次系統、書寫的開始與結束、刪字或選
字，以模擬一般的手寫和打字情境。
模型訓練所需要的資料包含全部符號各被眼寫多次所收集的原始資料
以及擴增資料，以 k 折交叉驗證（k-fold cross-validation）的方式訓練卷積
網路。使用者實際使用該系統時，可以辨識或選擇成功的符號軌跡可用來再
訓練，使模型更加穩健，越使用越符合使用者的書寫習慣，提高眼寫辨識的
準確率(Accuracy)。摘要(英) In patients with amyotrophic lateral sclerosis (ALS), due to the degeneration
of motor neurons, the muscles will gradually atrophy, lose exercise ability, and
cannot use oral and physical communication. Eye moving function that
degenerates later may become the only way for the later-stage patients to rely on
to communicate with others.
This study uses Arabic numerals (0~9), uppercase English letters (A~Z) and
4 special symbols (space, input, dot, question mark), a total of 40 symbols, to
establish the eye-writing system. This system uses electrooculography (EOG) to
record eye movements. It converts the EOG signals into images for symbol
recognition with a convolutional neural network (CNN). It uses the number of
blinks as special commands to control the entering and exiting of the writing and
recognition subsystem, the start and end of writing, character selection and
deletion. The system functions to emulate general handwriting and typing
situations.
The data required for model training include the original data collected by
eye-writing all symbols for multiple times and the augmented data. The CNN is
trained by k-fold cross-validation. When the system is practically used by the user,
any symbol trace that leads to successful character recognition or selection can be
used to retrain the neural network model to make the model gradually become
more robust. The more the system is used and retrained, the more it will fit the
user′s writing habits, and the accuracy of eye-writing recognition will be gradually
improved.關鍵字(中) ★ 眼電圖
★ 眼寫
★ 深度學習
★ 卷積網路
★ 數據擴增關鍵字(英) ★ EOG
★ eye-writing
★ deep learning
★ CNN
★ data augmentation論文目次 摘要........................................................................................................................i
Abstract................................................................................................................ii
目錄......................................................................................................................iii
圖目錄.................................................................................................................. vi
表目錄................................................................................................................viii
一、 緒論........................................................................................................... 1
1-1 研究動機................................................................................................... 1
1-2 論文架構................................................................................................... 1
1-3 文獻回顧................................................................................................... 2
二、 背景知識................................................................................................... 4
2-1 EOG 訊號 ................................................................................................... 4
2-2 其他眼動量測方法 ................................................................................... 6
2-3 眼動應用.................................................................................................... 7
三、 眼寫系統介紹........................................................................................... 8
iv
3-1 硬體設備.................................................................................................... 8
3-1-1 電極貼片 ............................................................................................ 8
3-1-2 儀表放大器 ........................................................................................ 9
3-1-3 右腳驅動電路.................................................................................. 10
3-1-4 高通濾波器 ...................................................................................... 11
3-1-6 低通濾波器 ...................................................................................... 12
3-1-5 反向加法器 ...................................................................................... 12
3-1-7 類比數位轉換器.............................................................................. 14
3-3 眨眼偵測.................................................................................................. 15
3-2 訊號處理.................................................................................................. 15
3-4 資料擴增.................................................................................................. 19
3-5 網路結構.................................................................................................. 22
3-6 系統操作.................................................................................................. 24
四、 實驗設置................................................................................................. 28
4-1 符號集...................................................................................................... 28
4-2 實驗人員.................................................................................................. 31
4-3 實驗項目.................................................................................................. 31
4-3-1 個人化系統 ...................................................................................... 31
v
4-3-2 資料擴增 .......................................................................................... 32
4-3-3 可選字及可再訓練.......................................................................... 32
五、 結果與討論............................................................................................. 33
5-1 個人系統.................................................................................................. 33
5-1-1 準確率 .............................................................................................. 33
5-1-2 混淆矩陣 .......................................................................................... 35
5-1-3 可靠度與可信度.............................................................................. 37
5-2 資料擴增.................................................................................................. 40
5-3 可選字及可再訓練 ................................................................................. 42
5-3-1 可選字 .............................................................................................. 42
5-3-2 再訓練 .............................................................................................. 42
5-4 與其他眼寫系統的比較 ......................................................................... 43
六、 結論與未來展望..................................................................................... 45
6-1 結論.......................................................................................................... 45
6-2 未來展望.................................................................................................. 46
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Engineering and Technology (ICET), pp. 1-6, 2017.指導教授 蔡章仁(Jang-Zern Tsai) 審核日期 2021-8-5 推文 plurk
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