本研究採用滑鼠為控制器，並經由調整滑鼠解析度的方式進行控制反應比的調控，探討控制反應比對移動目標物追蹤績效的影響。從實驗數據分析結果建立動態Fitts’ Law模式。實驗之後採用問卷方式了解受試者對控制反應比的偏好以及在動態追蹤作業使用之策略。
本研究實驗的控制器採用微軟2009年推出之遊戲專用滑鼠Side Winder X8 Mouse，並募集了10位受試者參與。實驗於十九吋液晶螢幕上以動態Fitts’ Law程式測試，分別在使用不同滑鼠解析度(250、1000、4000)的條件下，對不同目標物大小(6、9、12，單位：Dpi)、距離(20、40、60，單位：Dpi)以及速度(0、50、500，單位：Dpi/Sec)下進行追蹤作業，各種組合重複2次。實驗結果顯示，整體來說滑鼠解析度1000的績效(0.74秒)大於解析度250(0.84秒)大於解析度4000(0.89秒)，目標物大小與距離則符合Fitts’ Law模式，大小越大的績效(0.69、0.79、0.99秒)以及目標物距離(0.74、0.82、0.9秒)越近的績效越好，速度則為越慢績效越高(0.72、0.75、1秒)。
主觀評比的部分，整體而言受試者均偏好使用解析度1000之滑鼠，而使用之策略可分為兩種，分別為追擊的方式與預測路徑的方式，在使用解析度250與1000之滑鼠，針對移動速度較快的目標物受試者偏好使用預測路徑的方式；使用解析度4000之滑鼠，則僅目標物距離近時採用追擊的方式。
Fitts’ Law在預測本實驗之追蹤移動目標物的動作時間上，當目標物靜止時R2可達0.9，但是對移動中的目標物僅達0.3，顯示Fitts’ Law無法對動態目標物追蹤績效進行預設，而本研究發展出的動態模式對靜態或動態均可達到0.9。

This study examined the effects of changing control-response ratios on the performance of target acquisition with and without moving speeds. In addition, models were developed to express factors on the change of performance on target acquisition in the dynamic tasks. Questionnaires were used to understand participants’ strategies while traced these moving targets.

10 participants were requested to use Side Winder X8 Gaming Mouse (Microsoft) with different dpi settings (250, 1000, 4000 dpi), to trace target of 3 sizes (6, 9, 12, unit: dpi), in 3 distances (20, 40, 60, unit: dpi) and with 3 different speeds (0, 50, 500, unit: dpi/sec) on the 19” TFT-LCD. There was a repetition of two times for each level.

The result showed the mouse with 1000 dpi has the highest performance (0.74 sec) followed by 250 dpi (0.84 sec) and 4000 dpi (0.89 sec). Two strategies would be found, one is to trace and the other is to predict. Participants prefer to predict the path for the fast moving target under dpi 250 and 1000 dpi; whereas, participants prefer to trace for shorter distance while used mouse with 4000 dpi.

Traditional Fitt’s law was used to modeling performance time for moving targets and the mean R2 was as low as 0.3. Extended models were developed by incorporated moving speed and control-response ratios. As a result, they were better fit to the data with a mean R2 of 0.9

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