# Mind, Machine, and Meaning: Cognitive Ergonomics and Adaptive Interfaces in the Age of Industry 5.0
## 3 Ergonomic Techniques in Human-Machine Interactions
### Principles of Ergonomics Applied to Human-Machine Interactions
#### 3.1.2 Cognitive Ergonomics  
Cognitive ergonomics, as a discipline, addresses how mental processes such as perception, information processing, and decision-making affect performance and safety in human-machine interactions. In high-complexity work environments, operators are exposed to an increased informational density, requiring rapid perception and filtering of relevant cues--particularly under time pressure and stress, which can impair attention and lead to cognitive overload [43]. Studies confirm that mental workload correlates strongly with decision accuracy and task execution time, especially when perceptual ambiguity or multitasking is present [44]. Informational assistance systems, such as augmented reality (AR) and adaptive user interfaces, mitigate this by presenting visual guidance that reduces the burden on working memory and shortens decision paths [45].  
The design of collaborative robotic systems must integrate cognitive ergonomics from the early stages to align machine behavior with human cognitive capabilities. Systems that adapt based on the user's workload--measured through physiological signals such as eye movement, heart rate variability, or EEG (electroencephalography) --can enhance situational awareness and reduce the reaction time [29]. Decision-making in human-robot collaboration is influenced not only by task complexity but also by the level of system transparency and the avoidance of cognitive biases, such as confirmation or overconfidence bias, which have historically led to catastrophic errors in aviation and industry [46; 47]. Thus, cognitive ergonomics is not merely a safety factor but a foundation for trust, adaptability, and sustainable interaction in relation to Industry 5.0 developments.  
Figure 1 illustrates the sequential cognitive flow underpinning human-machine interactions, highlighting how humans perceive, interpret, and respond to information in real time. The process begins with external stimuli, such as visual or auditory cues, entering the perceptual system, where selective attention filters relevant inputs. These are then cognitively processed, evaluated, and interpreted based on the task context, memory, and experience. Once sufficient information is integrated, the user selects and executes a decision, which may involve a motor response (e.g., performing a button press) or a verbal command. This action, in turn, generates feedback either from the machine or the environment, which the user reinterprets, restarting the cognitive loop. Understanding this cycle is essential for ergonomic system design, as overload at any stage (especially perception or decision-making) can result in delayed reactions or critical errors [43].  
\begin{table}
\begin{tabular}{c c c} \hline
**Factor** & **Description** & **Impact on HMI** \\ \hline \multirow{2}{*}{Working Posture} & Misaligned or static body & Increases musculoskeletal \\  & positions during tasks & strain and task inaccuracy \\ \hline \multirow{2}{*}{Muscle Fatigue} & Local or systemic fatigue due to & Reduces performance and \\  & repetitive or high-load & increases risk of errors \\ \hline \multirow{2}{*}{Physical Load} & Manual handling, lifting, and & Leads to overexertion and \\  & force exertion & decreased task tolerance \\ \hline \multirow{2}{*}{Wearable Sensors} & IMU, EMG, and pressure-based & \\  & feedback for real-time & \\  & assessments & and ergonomic corrections \\ \hline \multirow{2}{*}{Haptic Feedback} & Vibrotactile cues guiding & Supports self-training and \\  & movement correction & ergonomic behavior learning \\ \hline \multirow{2}{*}{Cobots and HRC} & Collaborative robotics used to & \\  & reduce the biomechanical & Prevent WMSDs and \\  & workload & increase safety and comfort \\ \hline \end{tabular}
\end{table}
Table 1: Key physical ergonomic factors and their HMI relevance.