心電訊號(Electrocadiography，又簡稱為ECG)為心肌細胞進行極化與去極化時於身體表面產生的電位變化圖，原先廣用於心臟疾病的疾病上，但在近幾年生物辨識的需求與發展下，這個有別於臉孔與指紋辨識的生物特徵逐漸被研究者們注意。因為心電訊號平時由體內產生，且必須用特定的儀器才能進行量測，使得它相對於外顯性的指紋與臉孔特徵有著更高的安全性，又因為每個人的心肌結構不盡相同，這使得個體間的心電訊號擁有能與其他生物特徵媲美的辨識能力。在本研究，我們將利用一個基於單導程的心電訊號演算法，創建可刪式模板來進行後續的驗證動作，以形成一個用於識別使用者的認證系統(biometric verification system)。為了增加此系統的安全性，我們將在原本的演算法上，再套上第二因子認證模型上，經此結合的心電訊號雙因子認證系統，不僅可以達到高度的認證正確率，還能夠解決使用者輸入帳號密碼繁瑣的步驟，替使用者免去記憶上的煩惱。

Electrocardiograms (ECGs) are produced by the heart's electrical activity and are usually measured by the electrodes placed on the skin. They are widely used in detecting heart disease for healthcare. Thank the advance of technology, ECGs begin to play an essential role as biometrics. Having a verification rate similar to other biometric characteristics like fingerprints or faces, ECGs have several advantages. For example,they can only be measured by some specific instrument that must contact the human body, and thus, using ECGs to authenticate is safer than other biometrics on the way resisting spoofing from picturing. However, nowadays, the security of a system with only one authentication factor is not enough, so that we try to combine ECGs with the universal second-factor model to build up a system with high security and zero memory effort.

摘要 i
Abstract ii
致謝 iii
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1研究緣起 1
1.2論文架構 3
第二章 各式認證系統回顧 4
2.1傳統單因子認證與多因子認證系統 4
2.2 FIDO聯盟與通用第二因子認證模型 5
第三章 生物辨識與心電辨識演算法 7
3.1生物辨識與心電訊號 7
3.2心電訊號演算法 9
3.3可刪式生物辨識系統 10
3.4雙矩陣模板匹配演算法 11
第四章 系統架構與結果 13
4.1 系統架構 13
4.2 實體系統建構 17
4.3 演算法成效與壓縮後比較 21
4.4系統優劣比較 25
第五章 結論 28
參考文獻 29

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