# Determinants of Emotion Recognition System Adoption: Empirical Evidence from Malaysia
## 2 Literature Review
### ERS Applications  
ERS holds the potential to be applied in and bring benefits to various sectors due to its adaptability as an embedded technological function within a system. In other words, it can be one of the functionalities used to process the inputs of AI-enabled smart machines and computers to affect higher levels of HCI. ERS has been identified as having the potential to benefit the education sector as it can enable better engagement between instructors and learners [14; 37]. Emotions exert a noteworthy influence on academic performance, with positive emotions being particularly instrumental in enhancing student interest and focus and increasing the likelihood of academic success [37]. Instructors have derived benefits from using a webcam equipped with facial recognition technology within a computer to identify students' moods [14]. Another example of an ERS application is its integration into the implementation of a smart car [13]. A driver's performance can be influenced by their emotions, particularly given their impact on the driver's focus. Therefore, ERS has significance for applications to ensure driving safety. Specifically, [13] used a driving simulation with a built-in ECG modality in the steering wheels to detect human blood pressure in indicating emotional states of stress and fatigue. Similarly, the use of facial expressions for ERS towards video surveillance was proposed in [38]. It has been highlighted that video surveillance systems nowadays are operated via human capabilities to interpret behavior through video surveillance, which leads to delays in responding to emergencies [38]. The experiments concluded that the implementation of facial recognition as part of ERS towards video surveillance system can improve the reliability of abnormal behavior detection via facial expressions depending on different emotions and environmental conditions. Furthermore, facial expressions can be used in identifying pain, which will benefit the healthcare industry [39]. Assessing a patient's pain levels over time is deemed to be important, specifically regarding the effectiveness of medical treatments. Therefore, the usage of facial expression recognition can be widely anticipated in the healthcare industry. Physiological modalities have gained increased attention towards the successful implementation of ERS since physiological factors are more useful in understanding human emotions through neural activity [40]. Among physiological modalities, most of the methods have been assessed through healthcare facilities; therefore, the implementation of ERS through physiological modalities is more likely to be beneficial for the healthcare industry. Moreover, ERS applications in the healthcare industry can serve as a supportive aid for people with conditions like Down's syndrome and autism and among the elderly [41]. Multi-modal approaches combining facial expressions for automated emotion recognition and computer advisors guiding appropriate reactions to specific situations have been explored [41; 42]. Additionally, a communication aid using speech recognition was proposed to identify the tone and voice of special needs patients with conditions like autism or Down's syndrome [42]. However, given the accessibility of technologies, some components may be implemented in technological devices; thus, they can enhance global outreach to users. During the pandemic caused by COVID-19, some potential innovative solutions were introduced to enable technologies to be adopted in daily life, supported by virtual video-conferencing, which made breakthroughs and enabled working environments such as work from home, online classes, virtual event gatherings, and more [43]. Ref. [43] suggested that facial emotion recognition may provide a significant effect in reducing videoconferencing fatigue by analyzing participants in videoconferencing through Zoom; they tracked users using a facial recognition modality to recognize six emotions.