# Mind, Machine, and Meaning: Cognitive Ergonomics and Adaptive Interfaces in the Age of Industry 5.0
## 3 Ergonomic Techniques in Human-Machine Interactions
### Methodological Frameworks in HRA
#### 3.2.4 Eye-Tracking and EEG-Based Techniques in Ergonomic and Cognitive Research
For instance, changes in gaze trajectories and alpha brainwave activity have been correlated with engagement levels when assessing symmetrical product features or interface layouts [75]. In usability testing and human-computer interactions (HCIs), the combined use of EEG and ET facilitates the detection of moments when users experience cognitive strain or confusion. By analyzing gaze patterns alongside brainwave responses, designers can identify problematic interface elements and adjust them accordingly to reduce mental workload and improve efficiency [76]. Such methods also prove invaluable in assistive system design. [PERSON] et al. demonstrated the feasibility of a gaze-controlled system that allowed users with severe motor impairments to control home appliances and communicate through a visual interface, highlighting the accessibility potential of these technologies [80]. As a result, the study of design cognition has benefited significantly from biometric techniques. Researchers such as [PERSON] et al. have shown how EEG can be used to trace neural changes during different stages of creative thinking, with alpha suppression observed during ideation phases and increased theta activity during problem evaluation [78]. These results support a more detailed comprehension of the mental mechanisms involved in creative design and innovation. EEG and eye-tracking are also applied in the evaluation of cognitive loads during navigation and educational tasks. In the context of map learning, for example, [PERSON] et al. found that while fixation data alone may not distinguish between expert and novice users, saccade metrics and an EEG spectral analysis revealed elevated theta activity and decreased alpha activity during complex tasks, both recognized indicators of increased cognitive effort [77]. These insights help educators and interface developers tailor content to users' cognitive capacities, ultimately enhancing learning outcomes and user satisfaction. Limitations and Challenges  
Despite its strengths, this approach has the following technical and interpretative challenges [75; 76; 79; 80]:  
* EEG preparation time and movement sensitivity may hinder field deployment;
* Eye-tracking accuracy can be affected by lighting, screen size, or user posture;
* Requires multidisciplinary expertise in signal processing, design, and psychology;
* A risk of data misinterpretation if not triangulated with behavioral/contextual inputs;
* Nonetheless, newer wearable EEG devices and mobile ET systems are overcoming such barriers, promoting use in real-world environments. In conclusion, EEG and eye-tracking are complementary tools that enrich our understanding of human cognition, attention, and emotion in ergonomic and design contexts. Their integrated application allows researchers and engineers to decode not only what users focus on but also how they think and feel. As Industry 5.0 moves toward human-centered solutions, these techniques offer vital pathways to enhance safety, usability, and satisfaction in work systems.