近年來，步態分析已被廣泛運用於臨床，提供一個可量化的觀察，反應身體狀況所引起的步態週期變化，對於醫師，步態分析可作為診斷病灶的參考，用於觀察患者於治療前後恢復情形。
我們結合自行開發的步態分析軟體、感壓鞋墊、資料擷取器，建立一套穿戴式步態分析週期分析系統。穿戴式系統配置於腰部與腳踝，適合量測日常活動中的步態。我們以感壓鞋墊內的薄膜壓力傳感器，量測行進間的足壓訊號，透過訊號擷取器進行訊號蒐集、處理，再以Wi-Fi無線傳輸至個人電腦上的步態分析軟體。以模糊邏輯(Fuzzy logic method)轉換足壓訊號為可量化步態參數。
初步驗證步態模型的正確性，以健康受試者確認系統可行性，再用於分析膝關節病變患者術前，術後步態變化。針對施行高位脛骨平台截骨術膝關節炎患者的術前與術後兩組，比較不同組間未有顯著差異，因樣本數太少，個體差異大無法看到術前術後兩組的差異。我們更定期追蹤探討同一位患者於高位脛骨截骨術術前、術後數月步態的變化，確認術後的步態數據可反映臨床復原各階段的過程。

Gait analysis has been widely used in clinical applications, providing a quantifiable and observable information that can express the changes in the patient's gait caused by the syndrome on spine, lower limb or nervous system. For physicians, gait analysis can be used as a clinical usage in diagnosis, outcomes of the patient's physical recovery after treatment can be observed.
There are many electronic devices for gait analysis on market in last decade, but most of them are costy. Some medical centers founded the gait analysis laboratory, due to limited budget, regional hospitals may not afford to the cost of the system. With the advancement of electronic technology, the sensors and microcontrollers make self-developed gait analysis systems possible. Our study would develop the pressure-based gait analysis system, includes measured insoles, gait analysis software and portable data collectors. Fuzzy logic method is used to convert the foot pressure during walking into gait clinical parameters, which are applied to clinical.
In this study, 3 groups, including 15 healthy subjects, 11 knee Osteoarthritis(OA) patients, and 6 high tibial osteotomy(HTO) subjects were recruited to find out how HTO vary in gait, results show that there is no significant difference between OA and HTO group, and the healthy subjects are significantly difference from the they on walking speed and stride length. We can not claim that gait would change after HTO, the results only can describe in the subjects recruited in this study. The comparison results will be affected by individual differences in subjects and demographic factors, we still needs to collect more samples to get more convincing comparison results.
And 5 OA patients were recruited to find out personal gait change before and after HTO. The OKS and medical image analysis are used to describe the patient physical condition. The gait results show that the 4 of patients improve walking speed after surgery, and the remaining one slow down. The OKS results show that postoperative recovery of patient who slow down is not ideal, it took more time compare with the others. Medical images showed that the mechanical axis of him was overcorrected, like knee valgus. It can be the reason for the undesirable postoperative recovery and slower walking speed.

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