# How Do Humans Recognize the Motion Arousal of Non-Humanoid Robots?
## 4 Experiment One
### Discussion  
Different from previous studies that used machine learning algorithms to generate robot expressions and selected expression elements based on the robot's own detailed features, this research analyzes whether the amplitude of robot movement can be a general element that affects human recognition of NHR's arousal from the perspective of human cognition, based on Gestalt theory. By utilizing the kinematics constraint theory, widely applied in three-dimensional animation, existing NHRs are categorized into those dominated by IK constraint and those dominated by FK constraint. Previous studies have indicated that amplitude is helpful in recognizing arousal in NHRs dominated by IK constraint. This experiment validates that amplitude is also applicable to NHRs dominated by FK constraint when a motion consists of two segments with opposite directions. In the stages where amplitude plays a role, the recognition of arousal in NHRs by humans increases as the amplitude increases. The experimental results show that there is no significant difference in the recognition of arousal among the \"jump-phase-dominant group\", indicating that the \"jump phase\" is not the main motion phase affecting the recognition of amplitude; the results of the \"fall phase\" show that the recognition of arousal is in the order of large amplitude > medium \begin{table}
\begin{tabular}{c c c c} \hline
**Direction** & **Relationship** & **R Value** & \(p\)**Value** \\ \hline The Jump-Phase- & Amplitude and & & \\ Dominant Group & Arousal & & \\ The Fall-Phase- & Amplitude and & & \\ Dominant Group & Arousal & 0.680 ** & \textless{}0.001 \\ \hline \end{tabular}
\end{table} 
Table 4: Spearman Correlation Coefficient between Amplitude and Arousal in the Two Groups. **. At the 0.01 level (two-tailed), the correlation is significant. Figure 6: The position of arousal results in the emotional space. amplitude > small amplitude, which suggests that the \"fall phase\" plays a certain role in the participants' emotional recognition process. Thereby, we can draw conclusion 1: in non-humanoid robots with \"jumping\" and \"falling\" movements, the amplitude size of the \"fall phase\" is the main motion interval that affects the recognition of arousal. In further analysis of the jump-phase-dominant group, there were no significant differences in arousal levels within the group. It is known that the \"jump phase\" does not play a role, and all within the group have the same \"endpoint\" with a relatively high position (at the height of 1/3 of the total amplitude). This indicates that the \"endpoint\" plays a major role in the recognition of arousal levels, and increasing the position of the \"endpoint\" helps participants recognize a higher level of arousal. Inter-group comparisons also confirm this point: when falling from the same height, a higher endpoint position results in a higher recognition of arousal levels. Based on the above analysis, Conclusion 2 can be drawn: when the endpoint position is higher, the recognition of arousal levels is increased. The \"Peak-End Rule\" [48] suggests that people's impression of an event is primarily formed by the peak and the end stages of the event, with these two stages having the most profound impact on the overall experience. The results of this experiment, to some extent, resonate with this rule. That is, within a combined motion, the highest point reached by the motion's amplitude and the endpoint where the motion concludes play a significant role in the process of recognizing the arousal level of NHRs. To apply these findings to other robots, three points can be considered:  
Firstly, in other NHRs guided by FK, if there is a similar two-stage motion pattern, special attention should be paid to the amplitude and end position of the subsequent motion stage.