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DUX: a dataset of user interactions and user emotions
User experience evaluation is becoming increasingly important, and so is emotion recognition. Recognizing users’ emotions based on their interactions alone would not be intrusive to users and can be implemented in many applications. This is still an area of active research and requires data containing both the user interactions and the corresponding emotions. Currently, there […] -
Using facial emotion recognition to research emotional phases in an inquiry-based science activity
Background Observational and declarative approaches applied by human observers have dominated the study of emotions, engagement, and attention. However, these approaches are susceptible to biases such as social desirability. Additionally, declarative approach cannot measure these parameters in real-time. Purpose This study aims to apply Facial Emotion Recognition (FER) technology in an inquiry-based activity to address […] -
Systematic Evaluation of Driver’s Behavior: A Multimodal Biometric Study
Abstract Complex traffic areas and high cognitive workload while driving are leading contributors to traffic crashes. Even though cognitive workload and stress have been previously assessed through various neurophysiological responses, they are rarely characterized simultaneously, limiting the triangulation of behavioral metrics (like drivers’ visual attention and facial coding) with physiological measures to investigate their interplay. […] -
Alpha band prefrontal asymmetry does not underlie pain approach-avoidance: Results from two EEG studies approach-avoidance: Results from two EEG studies
Pain research is often focused on escape from pain or approach of relief, yet individuals with chronic pain make complex choices to face their pain to satiate other drives (approach-avoidance conflicts). An abundance of research has indicated that prefrontal alpha band asymmetry (PFA) underlies approach-avoidance in general, but there is limited information about whether PFA […] -
EEG-Based Neural Synchrony Predicts Evaluative Engagement with Music Videos
The use of neuroimaging to predict individual and population-wide behaviors, also known as neuroforecasting, was long applied to estimate movie popularity. Only recently, EEG-based neural synchronization, which is indicative of engagement, was found as a valid predictor of the listening behavior of the population. However, the population’s evaluative responses to the songs were not incorporated. […] -
Examining the Impact of Stress and Fear of COVID-19 on Transit Travel
The COVID-19 pandemic altered daily life by forcing governments to issue measures for the prevention of the spread of the disease such as stay-at-home orders, requiring face coverings, and maintaining physical distancing, among others. This caused a significant disruption in every aspect of people’s lives. This disruption was prominent in the transportation sector where travel […] -
The Process of Creating Interactive 360-Degree VR with Biofeedback
The paper aims to demonstrate the interconnectedness of filmmaking techniques and iterative software design methods during the creation of interactive 360-degree Virtual Reality (VR) scenarios. These scenarios, which were designed to treat social anxiety disorder (SAD), comprised of six distinct simulations. To track patients’ biodata, biosensors were integrated with the developed scenarios. In the paper, […] -
Using Machine Learning with Eye-Tracking Data to Predict if a Recruiter Will Approve a Resume
When job seekers are unsuccessful in getting a position, they often do not get feedback to inform them on how to develop a better application in the future. Therefore, there is a critical need to understand what qualifications recruiters value in order to help applicants. To address this need, we utilized eye-trackers to measure and […] -
A Multimodal Emotion Perspective on Social Media Influencer Marketing: The Effectiveness of Influencer Emotions, Network Size, and Branding on Consumer Brand Engagement Using Facial Expression and Linguistic Analysis
Social media influencers rely on emotional connection to maintain and grow their followings and have value for brands. To date, however, no research has quantitatively examined the impact of emotion in the facial expressions and caption text that influencers use in their video posts on consumer engagement through likes, comments, and views of posts. Grounded […] -
Designing Adaptive, Mixed-Mode HCI Research for Resilience
We describe the design of a mixed-mode study that illustrates an adaptive approach to conducting HCI research. This mixed-mode approach is resilient to circumstances created by public health crises such as the COVID-19 pandemic. We based our study around a web-based survey instrument that was used both online (N = 205) and in an HCI […]
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