生物辨識(Biometrics)一直在現代生活裡扮演著重要的角色，從個人電腦、筆記型電腦、門鎖系統甚至於提款機，到處皆可以見到生物辨識的應用。而每個人都有大腦，使用腦波辨識個人身份，是目前較新穎的研究目標。
支援向量機(Support Vector Machine, SVM)常被用來作訓練分類的人工智慧與機器學習方法，有效地處理回歸問題和模式識別等諸多現實問題。而在許多腦波相關研究，多使用支援向量機解決分類問題。
本論文使用低成本的腦波擷取裝置，並使用聲音當作刺激，提出一種新的特徵擷取方法結合支援向量機用在腦波辨識上，最後得到結果相當理想，證明利用聲音當作刺激是可以做為腦波辨識的一種方法。

Biometrics is playing a very important role in modern life. From personal computers, laptops, door-lock systems to automatic teller machines, biometrics can be seen applications within them. Everyone has brain, and using brainwaves to recognize each person is more newly research for now.
Support Vector Machine (SVM) is an Artificial Intelligence and Machine Learning tool which always used to train and classifies with different labels. For regression problems or pattern recognitions, Support Vector Machine can solve them efficiently and better than other Machine Learning systems.
In this thesis, we took an inexpensive Brain-computer Interface (BCI) and used sounds as stimulus for our brainwaves recognition system. We proposed a method combined with Support Vector Machine (SVM), and finally we got a well result such that prove using sound-stimulus can be a good way for brainwaves recognition.

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