# Research on the Parametric Design and Application of Ceramic Modeling Based on Python
## 3 Parametric Design Practice
### Determination of Parametric Design Factors
For EEG data, we extracted the power value of frontal lobe \(\theta\) waves (4-8 Hz) using the ErgoLAB EEG/ERP analysis module. This measurement helps evaluate the user's concentration on the ceramic design and the intensity of their emotional responses, with higher \(\theta\) wave power typically indicating positive emotions. For ECG and heart rate variability (HRV), we quantified users' emotional stability through time-domain and frequency-domain analyses, with the LF/HF ratio reflecting the balance between the sympathetic and parasympathetic nervous systems. For GSR data, we analyzed the skin conductance level (SCL) and event-related skin conductance response (ER-SCR) to identify users' instantaneous emotional arousal during design observation, such as surprise or stress. By combining these physiological parameters with eye movement  
Figure 2: ErgoLAB human–machine environment synchronization platform V3.0 experiment. data, such as gaze hotspot maps, we constructed a correlation model to link users' visual attention patterns with their emotional preferences for ceramic design elements. To ensure accurate data collection regarding participants' behaviors and responses, the experiment was designed with four task scenarios. First, participants freely observed ceramic samples with different design elements (such as glaze color, patterns, and shapes) for 30 s to record their natural visual attention distribution. Second, participants were required to choose their preferred option among multiple contrast samples (e.g., \"Shape A vs. Shape B\") and record the reasons for their choices to analyze the correlation between subjective preferences and physiological indicators. Third, participants simulated daily usage scenarios (e.g., holding a teacup to pour water) while motion capture and physiological signal analysis were used to assess operational comfort and cognitive load. Finally, the tasks were repeated under varying conditions of light (warm light vs. cold light) and observation angle (downward view vs. side view) to study the impact of environmental factors on user experience. During the human experiment, based on the obtained thermographic information, it was found that when the subject viewed the ceramic product from below, their visual attention was mainly focused on the cup rim shape; while at an oblique viewing angle, the changes in the outer contour curves corresponding to the axis of the ceramic product became the focal point of attention (see Figures 3 and 4). Based on the results of eye movement hotspots, gaze trajectory, gaze duration, and brain wave analysis of the ErgoLAB platform, several key factors in ceramic product shape design are established: (1) final radius and starting radius; (2) number of segments; (3) starting angle and ending angle; and (4) end height and start height. Among these, regarding the (1) final radius and starting radius, these two parameters in geometry, respectively, define the curvature characteristics of the terminal and initial points of a shaping curve or contour. The final radius, as a key indicator of the product's top shape, is directly related to the width and smoothness of the cup rim or top opening,  
Figure 4: Human–machine experiment hotspot map of experiment hotspot map. The shape outline curve. (The relationship between color and attention is the same as in Figure 3). Figure 3: Top shape human–machine. (Color temperature coding was used to represent the visual attention of ceramic parts. Warm colors (red/orange) corresponded to areas of high concern, reflecting visual significance. Cool colors (green/blue) indicate areas of low concern; Neutral tones (yellow/gray) indicate transition areas. Level contrast and gradient trend represent attention difference and dynamic change, respectively.) significantly impacting the overall proportion and visual focus of the product.