Product motion is a crucial design element, blending functionality with aesthetic appeal. Such motions establish an emotional bond between the product and its user. Engaging with the product stimulates curiosity and interest in its motion, encouraging repeated use. This study aims to formulate indicators for curiosity and interest in motion and to implement a computational system to generate motions that provoke inquiry. This study situates curiosity and interest as emotions crucial to the inquiry cycle, proposing that optimal prediction error (deviation from expected motion patterns) cultivates interest, while fluctuations in prediction error spark curiosity. Our analysis is based on the inquiry cycle, a mathematical model of emotions rooted in the free energy principle of brain function. We developed curiosity, motion, and interest measures from the model based on prediction error variation and reduction. The developed system can independently control prediction errors and their variations for a given open-loop mechanism. This system generates motions that control the magnitude of prediction errors by deviating from the trajectory of energy-minimizing motions. Using the semantic differential method and eye-tracking experiments measuring gaze duration, we found that interest correlates with prediction error in an upward-convex manner, and its variability induces curiosity. These results align with our model. The novelty of this study lies in experimentally verifying that applying moderate prediction errors and fluctuations in prediction errors is effective in increasing interest and curiosity in motion design. This research contributes design insights for engineers and designers seeking to enhance the appeal of product motions.