膝關節為人體最容易受傷之關節之一，而目前用來診斷膝關節病變的工具不是具有侵入性，就是無法有效地診斷出早期的軟骨病變。因此利用膝關節於擺動時所產生之振動訊號，來作為診斷依據的想法便相繼而生，而以此觀念而完成的文獻已達一定數量。
本論文旨在透過有系統的量測美國有氧體適能協會會員，藉由可適性區段與自迴歸模型，計算均方根值與平均內部群組距離兩特徵參數，並根據台大江清泉教授及其團隊所發表過之文獻，建立判斷膝關節受傷與否的準則。由這些準則可將所量得的資料分成正常、模糊與受傷三類，主要比對在兩特微參數下都被分類為正常與受傷的資料。再將這兩群資料之問卷內容擷取出來，根據不同的病歷情況做分類，由這樣的分類便可知道膝關節正常與受傷者人數各有多少，依序計算其在整體資料中所佔之比例，此比例即等於這些判斷準則的準確率。本論文的結果即在驗證文獻所建立資料庫之準確率，藉此舉期待能使膝關節聽診技術之發展更完整。

Vibroarthrograpyhy (VAG) is an innovative, objective and non-invasive technique to obtain diagnostic information concerning the articular cartilage of knee joints. Knee VAG signals can be detected by putting a contact sensor on the surface of the knee joints during the movement such as flexion and extension.
Before this research, there are many VAG group studies that contribute in signal processing and database building. The adaptive segmentation method and autoregressive modeling are developed to segment the nonstationary VAG signals. This thesis tries to investigate the accuracy of some database containing root mean square (RMS) value and intraclass distance (ID) feature parameters of physiological patellofemoral crepitus (PPC) signals.
This research is first setting up two diagnosis standards for RMS and ID. According to the two standards, all signals are divided into three types: normal, unknown and injured, and those appear both in normal type of RMS and ID parameters are picked out. The same does the injured type.
In conclusion, by checking the anamneses of these signals, we can be aware of the numbers of real normal and real injured in normal type and injured type; therefore the accuracy of the database can be derived. Consequently the accuracy of database in this thesis is quite certifiable.

中文摘要………………………………………………………………I
英文摘要………………………………………………………………II
目錄……………………………………………………………………III
表目錄…………………………………………………………………V
圖目錄…………………………………………………………………VII
第一章 前言……………………………………………………………1
1.1研究主題………………………………………………………1
1.2文獻回顧………………………………………………………3
1.3研究目的………………………………………………………10
1.4膝關節構造介紹………………………………………………11
1.5章節說明………………………………………………………15
第二章 基本理論……………………………………………………20
2.1膝關節於擺動下所產生的振動信號…………………………20
2.2膝關節振動訊號處理方法……………………………………22
2.2.1自迴歸（AR）模型……………………………………23
2.2.2可適性區段……………………………………………30
2.2.3均方根值（Root Mean Square；RMS）…………………32
2.2.4內部群組距離（Intraclass Distance）………………33
第三章 實驗方法與步驟……………………………………………34
3.1研究對象………………………………………………………34
3.2實驗儀器………………………………………………………35
3.3實驗步驟………………………………………………………38
第四章 實驗結果與討論……………………………………………47
4.1生理特性與特徵參數[44]……………………………………47
4.1.1均方根值與膝關節……………………………………47
4.1.2平均內部群組距離與膝關節…………………………48
4.2文獻結果彙整…………………………………………………49
4.3比對結果………………………………………………………52
4.3.1均方根值判定準則……………………………………52
4.3.2平均內部群組距離判定準則…………………………53
4.4分析結果與討論………………………………………………54
第五章 綜合討論與建議……………………………………………77
5.1綜合討論………………………………………………………77
5.2建議與未來展望………………………………………………79
參考文獻……………………………………………………………81

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