## 5 Result and Analysis
### Discussion  
This study evaluated the performance of different interaction techniques in terms of task completion time, cognitive load, and user satisfaction, yielding several key findings. First, the experimental results indicate that in terms of interaction efficiency, the Touch-Slider and Pinch-Slider methods, based on slider components, are significantly inferior to Bimanual Scaling, which utilizes a two-handed scaling action. This finding suggests that Touch-Slider and Pinch-Slider, traditional slider input methods, necessitate fine touch or pinch movements to adjust the slider, thereby increasing the operation's physical complexity and cognitive load. Conversely, Bimanual Scaling, through the user's two hands' natural collaborative movements for zooming in and out of the data range, significantly simplifies the operation and reduces hand-eye coordination stress, thereby enhancing interaction efficiency and lessening the cognitive burden. Furthermore, the intuitive interaction strategy of Bimanual Scaling diminishes the necessity for precise control, thereby enabling users to concentrate more on the task itself rather than on manipulating the interface. This enhances the interaction's naturalness and user satisfaction. Consequently, as an optimized method of interaction, Bimanual Scaling not only augments operational speed and efficiency but also improves the user experience. Second, in terms of cognitive load, the experimental findings demonstrate that the Gesture and Voice interaction method significantly reduces cognitive load, underscoring its capability to streamline operations and lessen the burden, particularly for scenarios that require users to multitask. From the perspective of interaction time, it was observed that both Bimanual Scaling and Keyboard interactions exhibited superior performance in input time. However, considering the subjective cognitive load, these methods did not demonstrate a significant advantage over the Touch-Slider and Pinch-Slider interactions. This may be attributed to the increased fatigue and cognitive stress from interacting with virtual objects and continuous adjustments of gestures. The Gesture and Voice interaction method enhances interaction efficiency through its intuitive and natural approach, reflected in both reduced objective interaction time and subjective cognitive stress dimensions. Bimanual Scaling offers a cohesive gesture input method, comparable to Keyboard interaction regarding both objective interaction time and subjective cognitive stress, yet demonstrates greater input efficiency. Conversely, Touch-Slider and Pinch-Slider interactions fall short in both efficiency and range, revealing notable deficiencies in data input performance. From the perspective of visual analytics applications, this study reveals the complexity of numerical input tasks in MR, emphasizing that interaction choices for data input in mixed reality interaction systems must be adjusted based on the usage environment. Among the five interaction methods discussed in this study, Gesture and Voice emerges as the method with the lowest cognitive stress and highest efficiency. However, in contexts like noisy environments or those requiring confidentiality, Gesture and Voice may not be optimal, underscoring the need for designers to account for environmental constraints and offer suitable alternatives [22]. Bimanual Scaling and Virtual Keyboard offer simple, rapid methods for brief, small-scale data input or when the Gesture and Voice method is impractical. These two methods demand less from the environment, especially Bimanual Scaling, which necessitates minimal hand-eye coordination and no extra space entities, offering a robust interaction mode for analyzing complex conditions like motion or confined spaces. However, designers need to pay particular attention to fatigue issues caused by continuous hand movements with these two interaction methods and avoid their use in long-duration, large-volume data entry tasks to prevent fatigue.