由於非侵入式腦波(EEG)偵測耳機之商業化，讓腦機介面(BCI)之領域與應用日漸普及，雖然使用腦波作為身分鑒別的應用仍然很少，不過不同個體間腦波清晰之差異使腦波成為身份鑑別可能的選項之一。身分鑒別的可靠程度決定了驗證系統的安全程度。然而對於「使用腦波作為身分鑑別」領域之論文進行調查時，我們發現，儘管系統最終都有十分良好的結果(精準度落在90 至 100% 左右)，然而這些研究中，對於腦波資料未進行最佳化前，精準度約落在60 至 70% 之間，或甚至更低。
我們希望從不同的面相對於腦波是否適合作為身分鑒別之選項進行測試。例如: 區分個體、區分所進行的活動，最後，對於分類演算法是否會產生不同的結果進行探討。

The availability of commercial non-invasive brainwave (EEG) headsets supports the growing popularity of BCI (Brain Computer Interface) domain. Although currently, only small interests among applications of applying brainwave as an authentication token, the clear presentation of brainwave between different individuals stand its foundation of a possible token for au-thentication. But, reliability of an authentication token is the basis of a reliable authentication system. We scanned through researches of using brainwave as authentication token and found that, although the final result of accuracy may vary a bit from 90% to 100%, in most cases, the result of accuracy without optimization may as low as 60% to 70%. We want to test the reliability of brainwave as an authentication token from a different perspective: Differenti-ate Individuals, Differentiate Activities, and finally, how results may differ between popular classification algorithms.

第一章　Introduction　　15
第二章　Related Works　　19
第三章　The Proposed Test　　25
第四章　Result　　43
第五章　Conclusion and Future Work　　49

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