多尺度熵（MSE）是一種近年來熱門的分析工具，用來代表多個尺度的時間序列複雜性，但較少利用此工具對不同輸入裝置的目標導向作業進行探討。本研究先回顧過去熵的概念、反覆運動及費茲定律相關研究，將實驗環境建立在費茲定律的框架下，進行顯示器環境設計、任務難度的定義及角度的設定，而實驗將分為兩種，實驗一為基礎的重複費茲反覆運動的目標導向作業，實驗二為包含角度因素的二維雙變量目標導向作業，透過動作捕捉系統（OptiTrack Motion Capture System）可將運動動作轉換成數位資料的特性，收集手部的運動軌跡，作為MSE分析的原始數據，以探討不同因子對於MSE的影響。其結果顯示，操控觸控筆的運動軌跡比操控滑鼠更具有複雜性；當任務需求增加時，其運動軌跡的複雜度會降低；當角度在大尺度時證實120-300度的運動軌跡比0-180度更複雜。期望透過本研究結果能為MSE應用於費茲反覆運動的作業上帶來貢獻。

Multiscale Entropy (MSE) is a popular tool for analysis to represent time series complexity at multiple scales in recent years. However, in MSE analysis there is a lack of relevant research on goal-directed tasks with input devices. In our study we review the relevant research in the concept of entropy, the reciprocal movement and the Fitts’ Law. Thus, the experimental environment is built under the framework of Fitts’ Law to design the display environment and define task difficulty and angle. The experiment is divided into two part. Experiment 1 is a basic repeated goal-directed task with reciprocal movement. Experiment 2 which considers the angle factor is a two-dimensional bivariate goal-directed task with reciprocal movement. By the OptiTrack Motion Capture System which can convert human characteristics into data, the trajectory of hand movement is collected for analysis to discuss the influence of different factors on the MSE. The results of the study were that the movement trajectory of using the stylus is more complex than mouse. When the task demand increases, the complexity of the movement trajectory will decrease. For angle factor, at large scale, it is confirmed that movement trajectory in 120-300 degree is more complex than 0-180 degrees. In the end, it is expected that the results of this study will contribute to the application of MSE.

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