# Sensors, Techniques, and Future Trends of Human-Engagement-Enabled Applications: A Review
## 7 Discussion
### Acceptance  
Human engagement estimation systems are rapidly gaining traction in diverse fields such as driver assistance systems, HRI, and digital engagement platforms as discussed in Section 6. However, the successful deployment of these systems hinges not only on their technical accuracy but also on their acceptance by end users. Recent research underscores the importance of incorporating user perspectives early in the design process to overcome adoption barriers. Failure to do so often leads to user resistance and dissatisfaction, impeding the successful deployment of new technologies [164; 165; 166]. Therefore, understanding the factors that influence user behaviour, motivation, and decision-making is crucial for fostering acceptance to engagement estimation systems. The Technology Acceptance Model (TAM) [167], developed by [PERSON], has been a cornerstone in understanding how users adopt and engage with new technologies. The TAM predicts user acceptance by focusing on key factors like perceived usefulness and perceived ease of use. These factors lead to an individual's attitude towards using the technology, which then influences their behavioural intention to use the system, and ultimately their actual use of it. In human engagement estimation, integrating the TAM into the design and development process can significantly raise the likelihood of user adoption [168; 169]. Perceived usefulness is critical in determining whether users find the technology beneficial in their specific context. For instance, driver assistance systems must allow users to perceive that engagement estimation can enhance their experience by appropriate warnings when detecting driver fatigue or distraction with few false positives [170]. In HRI, robots equipped with engagement estimation capabilities must demonstrate their ability to adapt to human emotions and behaviours [171], thereby improving interaction quality. Perceived ease of use plays a vital role in user acceptance by minimizing the learning curve associated with new technologies. For example, an engagement estimation system in a digital learning environment that is easy to integrate into existing educational tools [172; 173] and requires minimal efforts from educators is more likely to be adopted. Moreover, non-intrusiveness, where the system operates seamlessly without disrupting users' activities, enhances perceived ease of use. Users' attitudes towards using the system are influenced by factors such as trust, privacy, and ethical considerations [174; 175]. In human engagement estimation, these concerns are particularly salient due to the sensitive nature of the data collected. Users may refrain themselves from using the systems because of wariness of their private space being monitoring. Addressing these concerns through transparency, robust data security, and ethical safeguards can positively influence users' attitudes. Incorporating the TAM into human engagement estimation systems design highlights several challenges that must be addressed to ensure successful adoption [176]. Data privacy and security are paramount [177], given the sensitive nature of the collected data. Any perceived risks of data misuse can significantly hinder acceptance. Additionally, bias and fairness [178] in the algorithms must be carefully managed to prevent skewed or unfair outcomes, which could deter users from adopting the technology. The system's adaptability to different contexts and individual users is also crucial. The varying needs and expectations across different user groups mean that a one-size-fits-all approach is unlikely to succeed. Moreover, regulatory compliance with laws like the GDPR [179] is essential to avoid legal challenges and build trust with users. The behavioural intention to use an engagement estimation system is shaped by the perceived benefits relative to the effort required. If users believe that the system significantly improves their tasks, they are more likely to use it [163; 180].