.Post-partum hemorrhaging is a medical emergency that occurs during childbirth and, in extreme cases, can be life-threatening. It is the number one cause of maternal mortality worldwide. High-quality training of medical staff can contribute to early diagnosis and work towards preventing escalation towards more serious cases. Healthcare education uses manikin-based simulators to train obstetricians for various childbirth scenarios before training on real patients. However, these medical simulators lack certain key features portraying important symptoms and are incapable of communicating with the trainees. The authors present a digital embodiment agent that can improve the current state of the art by providing a specification of the requirements as well as an extensive design and development approach. This digital embodiment allows educators to respond and role-play as the patient in real time and can easily be integrated with existing training procedures. This research was performed in collaboration with medical experts, making a new contribution to medical training by bringing digital humans and the representation of affective interfaces to the field of healthcare.

There has been significant progress in the graphical realism of digital humans in recent years. This work investigates the realistic portrayal of emotions beyond facial expressions by analysing how skin colour changes when expressing different emotional states. The study combines existing knowledge from old painters, photogrammetry data, thermal imaging, and skin colouration maps to create an artistic guideline to portray emotions realistically, resulting in the proposal of a set of colour maps representing the six basic emotions. By using skin colour changes to represent emotional states, the proposed colour maps offer an alternative workflow for portraying emotions. During the experiment of this research four of these proposed colour maps, which represent neutrality, anger, disgust, and happiness, were preferred over traditional alternatives in terms of realism perception and likeability. The findings have implications for the development of digital human technology, particularly in the creation of more realistic and expressive digital characters.

Our study introduces an open general-purpose platform for the embodiment of conversational AI systems. Conversational User-interface Based Embodiment (CUBE) is designed to streamline the integration of embodied solutions into text-based dialog managers, providing flexibility for customization depending on the specific use case and application. CUBE is responsible for naturally interacting with users by listening, observing, and responding to them.

New online stores and digital distribution methods have led to the development of alternative monetization models for video-games, such as free-to-play games with advertisements. Although there are many games using such models, until now the effect on the player experience from such interruptions has not been studied. In this controlled experiment, we requested that participants (N=236) play one of three different versions of a platformer game with: 1) no interruptions, 2) 30-second video advertisements, and 3) a multiple-choice questionnaire. We then evaluated the effects on the player experience. The study shows differences in their experiences, namely in: competence, immersion, annoyance, affects, and the reliability of the questionnaire answers. The contribution of this work is to identify which player experience variables are affected by interruptions, which can be valuable for selecting the business model and guiding the game design process.

Trying to understand a player's characteristics with regards to a computer game is a major line of research known as player modeling. The purpose of player modeling is typically the adaptation of the game itself. We present two studies that extend player modeling into player profiling by trying to identify abstract personality traits, such as the need for cognition and self-esteem , through a player's in-game behavior. We present evidence that game mechanics that can be broadly adopted by several game genres, such as hints and a player's self-evaluation at the end of a level, correlate with the aforementioned personality traits. We conclude by presenting future directions for research regarding this topic, discuss the direct applications for the games industry, and explore how games can be developed as profiling tools with applications to other contexts.

Research studies and recruitment processes often rely on psychometric instruments to profile respondents with regards to their ethical orientation. Completing such questionnaires can be tedious and is prone to self-presentation bias. Noting how video games often expose players to complex plots, filled with dilemmas and morally dubious options, the opportunity emerges to evaluate player’s moral orientation by analysing their in-game behaviour. In order to explore the feasibility of such an approach, we examine how users’ moral judgment correlates with choices they make in non-linear narratives, frequently present in video games. An interactive narrative presenting several moral dilemmas was created. An initial user study (N = 80) revealed only weak correlations between the users’ choices and their ethical inclinations in all ethical scales. However, by training a genetic algorithm on this data set to quantify the influence of each branch on recognising moral inclination we found a strong positive correlation between choice behaviour and self-reported ethical inclinations on a second independent group of participants (N = 20). The contribution of this work is to demonstrate how genetic algorithms can be applied in interactive stories to profile users’ ethical stance.

Self-esteem is a personality trait utilized to support the diagnosis of several psychological conditions. With this study we investigate the potential that computer games can have in assessing self-esteem. To that end, we designed and developed a platformer game and analyzed how in-game behavior relates to Rosenberg's Self-Esteem Scale. We examined: i) how a player's self-esteem influences game performance, ii) how a player's self-esteem generally influences in-game behavior iii) the possible game mechanics that assist in inferring a player's self-esteem. The study was conducted in two phases (N=98 and N=85). Results indicate that self-esteem does not have any impact on the player's performance, on the other hand, we found that players' self-evaluation of game performance correlates with their self-esteem.

Player behavior during game play can be used to construct player models that help adapt the game and make it more fun for the player involved. Similarly in-game behavior could help model personality traits that describe people's attitudes in a fashion that can be stable over time and over different domains, e.g., to support health coaching, or other behavior change approaches. This paper demonstrates the feasibility of this approach by relating Need for Cognition (NfC) a personality trait that can predict the effectiveness of different persuasion strategies upon users to a commonly used game mechanic -- hints. An experiment with N=188 participants confirmed our hypothesis that NfC has a negative correlation with the number of hints players follow during the game. Future work should confirm if adherence to hints can be used as a predictor of behavior in different games, and to find other game mechanics than hints, that help predict user traits.