髂前上棘定位量測

Abstract

長短腳可以劃分為結構性長短腳與功能性長短腳，其中功能性長短腳的量測方法一般為自髂前上棘量至腳外踝，判斷主要靠人工量測，其方法為以觸摸的方式定位出髂前上棘(Anterior superior iliac spine)與腳外踝的最凸點，再利用皮尺量測兩點的距離，即為認定之腳長，此方法容易因人為判斷差異導致不同之量測結果。目前較準確之量測方法有X光、CT、3D US、MRI，但是這些方法有輻射危害或是價格昂貴等缺點，本研究之目的是要開法一套廉價，無輻射危害的機械化量測裝置，針對功能性長短腳的量測中，利用機械方式定位出髂前上棘。此量測系統分為量測裝置與LabVIEW程式兩部分。量測裝置是利用附加量測探頭的荷重元與位移計，經由DAQ擷取器抓取量測體的軟組織或骨頭組織的數據，再用LabVIEW程式分析量測點在不同受力下的剛性變化率與Z軸絕對位置，得出一個總結達到定位ASIS此目的。如何從量測數據中分析出有效的結果，為此實驗最大的挑戰，為解決此問題，將對每一個量測點重複做10次量測，並利用五種取樣方式來找尋適合的代表樣本，方法分別為: (1)10組數據同時嵌合1條方程式(2)10組數據分別嵌合1條方程式再平均出1條平均方程式(3)從10組數據隨機抽取1組數據嵌合1條方程式(4)取第1組數據嵌合1條方程式(5) 取第2組數據嵌合1條方程式。以此不同的取樣在不同的受力區段下做多方嘗試的綜合分析。研究中總共量測6個量測體，BMI介於20 kg/m2∼28.2 kg/m2，目前整體量測髂前上棘的定位結果與人工定位之最大誤差為5 mm。

Leg length discrepancy(LLD) can be classified into two categories. One is structural leg length discrepancy and the other is functional leg length discrepancy. The functional leg length discrepancy measurement method relies on manual measurements. The different measurement results would happen by human judgment. At present, more accurate methods of measuring are X-ray、 CT、 3D US、 MRI, but these methods are expensive radiation hazards and the other disadvantages .So we want to develop a mechanized measurement device which avoids radiation dangerous and high prices in this study so that we can position anterior superior iliac spine(ASIS) which is reference point in functional leg length discrepancy measurement. The gauging system includes two parts: gauging devices and LabVIEW. The gauging devices includ a load cell with probe and a displacement meter, crawled body muscle or bone tissue data by DAQ devices. Use different sampling analysis the situation that under a different force change how the rigidity change and Z axis absolute position response by LabVIEW program. With this result we can make a summary to locate the ASIS. How to analyze valid result in measured data is the biggest challenge for this experiment .In order to solve this problem, Each measurement point will repeat 10 times of measurements and using five ways to find suitable representative sample, methods below: (1) 10 sets of data simultaneously fitting an equation (2) 10 sets of data respectively fitting an equation and averaged an mean equation (3) randomly selected a set of data from the 10 sets of data and fitting an equation (4) selected the first set of data fitting an equation (5) select second sets of data fitting an equation. So that we can make comprehensive analysis by different sampling. In this study, we have six measuring body, BMI is between 20 kg/m2~ 28.2 kg/m2, the current overall measurement of the anterior superior iliac spine positioning results compared to manual positioning maximum error is 5 mm.