在本研究中採取了正零越點區間方法，並採取心率異變率特徵中的 10 種時域特徵，
用於癲癇發作預測。在研究中發現這些特徵有幾個特徵對於癲癇腦波相當有用，但是也 有一部分特徵沒被使用到，並且在一部分病人的表現上也不是相當理想，在分類器上選 擇，隨機決策森林、貝氏分類器、最近鄰居法、支持向量機、線性識別分析等五種，利 用這些分類器去對那些特徵做分類，在訓練的方面消耗大量的時間。
綜合上述幾點，在未來可以針對效果較好的 HRV 時域特徵去做更深度的研究，找到 符合大多數病人的特徵，另一方面在分類器的部分，可以進一步的去探討那些分類器可 以快速有效的分類出這些特徵，具有更好的效率，在訊號分段上還能更深入的去研究，
找到更好的分段秒數，這些都是未來希望能夠改進。
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