Examining User Emotions in Human-Computer Interaction Studies Through Psychological Indicators
In a recent study, researchers have delved into the world of Human-Computer Interaction (HCI) to explore the psychophysiological measures that best represent the dimensions of emotional experiences. The paper presents an approach to studying the tendency of a user's emotion, aiming to assist HCI researchers in conducting HCI experiments more effectively.
The study, focusing on hedonic experiences that provide pleasure and positive emotions, used a combination of three non-invasive psychophysiological measures: Electroencephalography (EEG) for brain wave analysis, Facial expression/facial coding, and Eye tracking. Other measures included Galvanic skin response (GSR) or electrodermal activity, Heart rate variability (HRV), Electrocardiography (ECG), and Electromyography (EMG). These signals have been widely used and are approximately equally represented in studies assessing user experience and emotional dimensions in Virtual Reality (VR) and HCI contexts.
EEG provides valuable insights into neural activity related to emotional states and cognitive processes, making it a primary physiological measure for usability and emotional experience evaluation. Facial expression coding and emotion recognition via facial data offer non-invasive measures closely linked to emotional valence and intensity. Eye tracking helps in evaluating attentional allocation and arousal components of emotion, crucial in User Experience (UX) research. GSR reflects sympathetic nervous system arousal, indexed to emotional intensity or stress, while HRV measures autonomic nervous system balance, relating to emotional regulation and stress responses. EMG can capture muscle activity related to emotional expressions or tension.
By combining these multiple signals, the researchers were able to perform a multidimensional mapping of emotional experiences, often along dimensions like valence (positive-negative), arousal (activation), and dominance/control, which are central to emotional modeling in HCI research.
The experiment conducted for this paper used both quantitative and qualitative data analysis to determine the correlation between these psychophysiological measures and the main dimensions of emotion (valence and arousal). The results showed significant correlations that are crucial for the proposed approach.
While the study verifies the correlation of psychophysiological measures with both valence and arousal, the findings do not reach a definitive conclusion on which psychophysiological measure best represents the emotion's dimensions. This highlights the need for further research in this area.
The paper's approach could be useful for researchers seeking to study the emotional responses of users in HCI experiments more comprehensively. The potential implications of these findings could lead to improvements in the design of user-friendly and emotionally engaging interfaces in HCI. Furthermore, the study's findings could potentially contribute to the development of more accurate and effective emotion recognition systems in HCI.
[1] Smith, A., & Woolley, S. (2020). Psychophysiological Measures in HCI: A Review of Methods and Applications. ACM Transactions on Interactive Intelligent Systems, 10(4), Article 27. [2] Kringelbach, M. L., & Berridge, K. C. (2019). Neurochemistry of Hedonic Experiences. In The Oxford Handbook of Hedonic Psychology (pp. 175-194). Oxford University Press.
- This study, delving into technology-centered fields like Virtual Reality and Human-Computer Interaction, utilizes science to analyze emotional dimensions by employing various non-invasive psychophysiological measures such as Electroencephalography, Facial expression/facial coding, and Eye tracking, aiming to refine mental-health research in these domains.
- In health-and-wellness discourse, the integration of these psychophysiological measures offers a deeper understanding of emotional experiences, with the potential to foster technology designs that respond sensitively to users' emotional states and promote user-friendly, emotionally engaging interfaces.
