## 7 Discussion and Analysis
### Visualization of Emotional Features in Autistic Children  
This study uses the gradient-weighted class activation mapping (Grad-CAM) algorithm to generate heat maps to visually represent the significant basis for model prediction. The darker red color displayed on the heat map signifies a greater contribution and heightened response of the region to the emotion recognition model, which serves as the primary foundation for discriminating emotions in the model. Figure 13 presents Grad-CAM heat maps visualizing the critical facial regions that influence the model's emotion recognition decisions for children with autism. In these visualizations, red areas represent regions of high activation that strongly contribute to classification decisions, while blue areas indicate regions with minimal contribution. Analysis of these activation patterns reveals consistent attention distributions across different emotional states, as follows:  
Figure 13: Grad-CAM visualization of facial expression features across four emotional states in children with autism. Each row represents a different emotion (calm, happy, sad, and angry), with multiple samples shown. Red regions indicate areas of high importance for the model’s classification decisions, while blue regions represent areas of lower relevance. 1. For calm emotions (first row), the model demonstrates distributed attention across multiple facial areas, with particular focus on the upper cheeks, forehead, jaw regions, and nasolabial folds. This pattern suggests that neutral emotional states in children with autism are characterized by subtle features distributed across the face rather than concentrated in specific expressive regions. 2. For happy emotions (second row), the model consistently emphasizes sensory regions and their surrounding areas, particularly the eyes, mouth, and periorbital muscles. The activation patterns show concentrated attention on smile-related features, including the corners of the mouth and the orbicularis oculi muscles that are activated during genuine expressions of happiness. This finding aligns with previous research indicating that children with autism may express happiness through characteristic eye and mouth movements, albeit with different muscular coordination than typically developing children [9]. 3. For sad emotions (third row), the model exhibits targeted attention to specific sensory regions, predominantly focusing on the eyes, mouth, and nasal areas. The consistent activation around the eyes and the downturned mouth corners corresponds to the characteristic facial configurations associated with sadness. This localized attention pattern suggests that children with autism express sadness through distinctive movements in these specific facial regions rather than through global facial configurations. 4. For angry emotions (fourth row), the model demonstrates more holistic attention patterns spanning across broader facial regions, with activation distributed across the brow, eyes, and mouth areas. This comprehensive attention distribution suggests that anger expression in children with autism involves coordinated movements across multiple facial regions, though with activation patterns that may differ from those observed in typically developing children. These visualization findings provide important insights into how the model interprets the facial expressions of children with autism. The observed attention patterns confirm the findings of previous research suggesting that children with autism rely more on specific facial regions for emotional expression rather than coordinated global facial movements ([PERSON] et al., 2016 [9]; [PERSON] et al., 2015 [7]). Furthermore, these visualizations offer a quantitative basis for understanding the distinctive facial expression characteristics in this population, potentially informing both diagnostic approaches and therapeutic interventions targeting emotional communication. The analysis of misclassification patterns revealed important insights into the model's limitations.