在現今時代，社會逐漸往高齡化發展，老人養護在最近幾十年開始受到大家重視，當年紀越大，肌耐力、專注力、體力都不可避免的下降，使得大大提高老人跌倒的風險。由於跌倒是造成老人死亡的高風險原因，評估一個人的平衡能力成了重要的課題，為達成該目標，透過該人在平衡站立受到外力干擾時，量測其姿勢的響應做為評估的動態姿勢圖，相對的，靜態姿勢圖則量測該人不受外力干擾時的穩定站立情形。
本文主要是觀察靜態姿勢特徵和動態姿勢特徵之間可能的關聯性，藉由在12處肌肉得到之EMG訊號，動態姿勢特徵採用IEMG和Latency Time；另外根據測力板的量測，靜態姿勢特徵為傳統COP指標和本文發展指標。
透過干擾11位受測者在前進和後退時的穩定靜止站立，該實驗結果發現在靜態和動態的姿勢特徵於方向(前進和後退)和肌肉(12塊肌肉)間是相依的，該結果可應用於藉著得到的靜態姿勢特徵來預測可能的動態姿勢，因為靜態特徵是比動態特徵更簡易獲得。

In recent centuries, the average life expectancy has significantly increased. Our society is thus becoming an aging society. Therefore, the nursing problem for elder people has received a lot of attention. When people get older, their muscle strength, focus ability, and physical strength inevitable decline. As a result, the risk of falling increases significantly with aging. Since falling is an independent risk factor of death for elder people, preventing falling by evaluating the balance ability has becoming an important issue.
To toward this goal, dynamic posturography evaluates postural stability by disrupting a stable stance and measuring the postural response to such external perturbations. In contrast, static posturography measures the postural steadiness of the human body without any external excitation.
To goal of this work is to investigate the possible correlations between the static and dynamic posturography features. Extracted from the EMG signals measured from 12 different locations, the dynamic posturography features employed in this study include IEMG and latency-time. Based on the measurements of a force platform, the employed static posturography features include conventional COP features and features developed in this work.
By disrupting the stable stance of 11 tests subject from both forward and backward directions, the experimental results find outs that correlations between the static and dynamic posturography features are direction and muscle dependent.
A possible application of these results is try to predict the performances of dynamic posturography by using the results obtained from static posturography since the latter is much simpler to perform than the former.

論文審定書 i
誌謝 ii
摘要 iv
Abstract v
目錄 vii
圖次 x
表次 xii
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 1
1.3 文獻回顧 2
1.4 論文架構 3
第二章 實驗方法與流程 4
2.1 實驗對象 4
2.2 實驗設計 5
2.3 實驗架構 7
2.4實驗方法 8
2.4.1 人機介面設計 8

2.4.2 測力板&EMG訊號啟動點 14
2.4.3 測量方法 15
第三章 分析流程與方法 16
3.1 假設檢定(Hypothesis Test) 16
3.2 相關係數(Correlation coefficient) 18
3.3 分析流程 19
3.4 分析方法 20
3.4.1 積分肌電圖 22
3.4.2 Latency Time 22
3.4.3 Mean Correlation (MC) 23
3.4.4 Zero crossing number (ZCN) 23
3.4.5 Mean Distance 24
3.4.6 Range 24
3.4.7 Fz- Zero Crossing 24
3.4.8 Fractal Dimension-FD 25
3.4.9 Circle Area 25
3.4.10 IndexB 26
3.4.11 IndexF 26
3.4.12 Ellipse Area 27

3.4.13 Sway Area 27
3.4.14 Mean Velocity 27
3.4.15 Mean Frequency 28
3.4.16 Fractal Dimension-CE 28
3.4.17 Fractal Dimension-CC 28
3.4.18 Velocity_AP 29
3.4.19 Velocity_ML 29
3.4.20 Entropy 29
第四章 分析結果 30
4.1 肌肉關聯性 31
4.2 測力板啟動前與肌肉啟動後2秒 37
4.3測力板啟動前與肌肉啟動後最小時間區段 41
4.4 力板啟動前與肌肉啟動時間差 44
4.5 力板啟動後與肌肉啟動後2秒 48
第五章 結論與未來展望 50
參考文獻 51
附錄 I 肌肉啟動後2秒與測力板全部參數之相關性 53
附錄 II 肌肉啟動後最小時間區段與測力板全部參數之相關性 60
附錄 III 肌肉啟動時間差與測力板全部參數之相關性 67

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