## 2 Literature Review  
In this section, we discuss the scientific literature on cognitive workload, perceived stress, user acceptance and trust in HRC to help readers to understand their impacts on users and why it is crucial to focus on these elements when designing and implementing CAS. Cognitive workload is a cognitive state described as a proportion between the operator's available cognitive resources and the cognitive demands of the task [25]. With limited cognitive resources, excess demands could be a risk factor that affects workers' safety [26] and performance [27]. Previous research on cognitive overload, which is defined as a state of high cognitive workload [28], showed mixed results, with some studies considering it desirable [29] and others considering it harmful [30]. According to [30], high levels of cognitive workload due to mental fatigue or inattention interfere with the assembly task, resulting in a longer processing time and higher muscle activity. High levels of cognitive workload can also impact gaze behaviour, as some authors found an association with longer fixation durations and a lower frequency of fixations [31]. On the other hand, a low workload occurs when few resources are required to complete the task and many resources are available. Although less prevalent, it can still affect performance, reducing alertness and attention [25]. In this scenario, an appropriate level of cognitive workload needs to be targeted to manage the impact on the operator, especially in terms of performance and safety. In the present study, we aimed to investigate the effect of workstation and interaction design features on cognitive workload using subjective and objective metrics and their relationship with factors such as technology acceptance and perceived stress. Perceived stress is predicted by cognitive workload [23], with both constructs fundamentally influencing both safety and performance, as they lead to human errors. The transactional model of stress and coping views stress as a mismatch between external demands and individual resources [32]. This definition emphasises the crucial importance of the person's interpretation of an event (i.e., whether it is threatening or not) and whether the external and internal pressures exceed available resources and the ability to cope with them. In the HRC context, the robot's human likeness and proximity are the main stressorsleading to a biological response. Ref. [33] highlighted that minimum-jerk trajectories (MJTs), which is a robot-motion-planning system that minimises acceleration changes and human effort, help to decrease the operator's levels of perceived stress, as they are considered familiar and predictable. [PERSON] et al. [34] found that when designing a system, it might be important to limit the human-robot relative distance and the robot's speed, which should report its movements in advance. The efficacy of the robot's notifications before conducting a behaviour is useful, as humans are negatively affected by non-predictable robot movements, scoring lower well-being and performance scores [35; 36; 37]. It could be argued that individuals that are more accepting of technology may be more likely to use it, resulting in less cognitive workload and stress when engaging with technology. In addition, individuals are less likely to feel stressed when they believe that technology is helpful and easy to use. In contrast, individuals who have a negative attitude towards technology are more likely to reject it and, therefore, find using it stressful. This is because they perceive the technology as difficult to use or unhelpful. Acceptance is \"the demonstrable willingness within a user group to employ the technology for the tasks it is designed to support\" [38]. The main model addressing this topic is the technology acceptance model (TAM), theorised by [39], who proposed the key role of two factors: perceived usefulness and perceived ease of use.