Emotion Recognition System Adoption: A Proposed Framework

Abstract

An emotion recognition system or ERS is an emerging technology due to its potential use in various platforms, applications and sectors. ERS is a key technology arising from the fourth industrial revolution (IR 4.0) and arguably it is becoming a key technology in enabling the fifth industrial revolution (IR 5.0). This is so because IR 5.0 main feature is personalization. The body of knowledge on ERS consists largely of works on exploring the modalities or modes to recognise or determine emotion; the development of the system itself; and the creation of applications utilising the emotion recognition functions. However, to enable the researchers and innovators to develop better and more impactful ERS, they need to understand the factors shaping usage and determining adoption amongst the intended users. This particular aspect relating to ERS is not yet fully explored and understood. Plus, there is yet to be a definitive framework or model on determinants for ERS adoption. This research intends to address this important need. Specifically, this study will look into the key adopters that will be using ERS, and propose a conceptual framework for ERS adoption. The theories underpinning the proposed conceptual framework are the Theory of Planned Behaviour (TPB), Unified Theory of Acceptance and Use of Technology (UTAUT) and Diffusion of Innovations (DOI). It is envisioned that this research will; confirm the validity of the proposed framework and generate new findings that will benefit ERS practitioners as well as adopters.

Determinants of Emotion Recognition System Adoption: Empirical Evidence from Malaysia

“…This paper expands upon our preliminary study [76], refining the research framework and objectives. Figure 2 presents the finalized research framework with 10 hypotheses.…”

Particle Swarm Optimisation for Emotion Recognition Systems: A Decade Review of the Literature

“…One of the main highlights that benefit from ERS is in healthcare industries [17], developed the modalities of ERS and suggested their applications in healthcare. Researchers used facial recognition combined with ECG to identify the six basic emotions [27]. Furthermore, ERS has been suggested to provide better health services quality assurance by facilitating decision-making throughout the COVID-19 pandemic by allowing safe monitoring and higher emotional awareness among the practitioners [26,27].…”

“…Researchers used facial recognition combined with ECG to identify the six basic emotions [27]. Furthermore, ERS has been suggested to provide better health services quality assurance by facilitating decision-making throughout the COVID-19 pandemic by allowing safe monitoring and higher emotional awareness among the practitioners [26,27]. Furthermore, according to [28], social robots have risen to facilitate limitations due to COVID restrictions.…”