Research on financial decision-making shows that traders and investors with high emotion regulation capabilities perform better in trading. But how can the others learn to regulate their emotions? ‘Learning by doing’ sounds like a straightforward approach. But how can one perform ‘learning by doing’ when there is no feedback? This problem particularly applies to learning emotion regulation, because learners can get practically no feedback on their level of emotion regulation. Our research aims at providing a learning environment that can help decision-makers to improve their emotion regulation. The approach is based on a serious game with real-time biofeedback. The game is settled in a financial context and the decision scenario is directly linked to the individual biofeedback of the learner’s heart rate data. More specifically, depending on the learner’s ability to regulate emotions, the decision scenario of the game continuously adjusts and thereby becomes more (or less) difficult. The learner wears an electrocardiogram sensor that transfers the data via Bluetooth to the game. The game itself is evaluated at several levels.

Traders and investors are aware that emotional processes can have material consequences on their financial decision performance. However, typical learning approaches for debiasing fail to overcome emotionally driven financial dispositions, mostly because of subjects' limited capacity for self-monitoring. Our research aims at improving decision makers' performance by (1) boosting their awareness to their emotional state and (2) improving their skills for effective emotion regulation. To that end, we designed and implemented a serious game-based NeuroIS tool that continuously displays the player's individual emotional state, via biofeedback, and adapts the difficulty of the decision environment to this emotional state. The design artifact was then evaluated in two laboratory experiments. Taken together, our study demonstrates how information systems design science research can contribute to improving financial decision making by integrating physiological data into information technology artifacts. Moreover, we provide specific design guidelines for how biofeedback can be integrated into information systems

This study investigates individuals’ cognitive load processing abilities while engaged on a decision-making task in serious games, to explore how a substantial cognitive load dominates over the physiological arousal effect on pupil diameter. A serious game was presented to the participants, which displayed the on–line biofeedback based on physiological measurements of arousal. In such dynamic decision-making environment, the pupil diameter was analyzed in relation to the heart rate, to evaluate if the former could be a useful measure of cognitive abilities of individuals. As pupil might reflect both cognitive activity and physiological arousal, the pupillary response will show an arousal effect only when the cognitive demands of the situation are minimal. Evidence shows that in a situation where a substantial level of cognitive activity is required, only that activity will be observable on the pupil diameter, dominating over the physiological arousal effect indicated by the pupillary response. It is suggested that it might be possible to design serious games tailored to the cognitive abilities of an individual player, using the proposed physiological measurements to observe the moment when such dominance occurs. © 2018, The Author(s).

The aim of this paper is to investigate performance in a collaborative human–robot interaction on a shared serious game task. Furthermore, the effect of elicited emotions and perceived social behavior categories on players’ performance will be investigated. The participants collaboratively played a turn-taking version of the Tower of Hanoi serious game, together with the human and robot collaborators. The elicited emotions were analyzed in regards to the arousal and valence variables, computed from the Geneva Emotion Wheel questionnaire. Moreover, the perceived social behavior categories were obtained from analyzing and grouping replies to the Interactive Experiences and Trust and Respect questionnaires. It was found that the results did not show a statistically significant difference in participants’ performance between the human or robot collaborators. Moreover, all of the collaborators elicited similar emotions, where the human collaborator was perceived as more credible and socially present than the robot one. It is suggested that using robot collaborators might be as efficient as using human ones, in the context of serious game collaborative tasks.

This paper sets out to examine how elicited physiological affect influences the performance of human participants collaborating with the robot partners on a shared serious game task; furthermore, to investigate physiological affect underlying such human-robot proximate collaboration. The participants collaboratively played a turn-taking version of a serious game Tower of Hanoi, where physiological affect was investigated in a valence-arousal space. The arousal was inferred from the galvanic skin response data, while the valence was inferred from the electrocardiography data. It was found that the robot collaborators elicited a higher physiological affect in regard to both arousal and valence, in contrast to their human collaborator counterparts. Furthermore, a comparable performance between all collaborators was found on the serious game task. © 2018, IFIP International Federation for Information Processing.

Evidence shows that emotions critically influence human decision-making. Therefore, emotion-regulation using biofeedback has been extensively investigated. Nevertheless, serious games have emerged as a valuable tool for such investigations set in the decision-making context. This review sets out to investigate the scientific evidence regarding the effects of practicing emotion-regulation through biofeedback on the decision-making performance in the context of serious games. A systematic search of five electronic databases (Scopus, Web of Science, IEEE, PubMed Central, Science Direct), followed by the author and snowballing investigation, was conducted from a publication's year of inception to October 2018. The search identified 16 randomized controlled experiment/quasi-experiment studies that quantitatively assessed the performance on decision-making tasks in serious games, involving students, military, and brain-injured participants. It was found that the participants who raised awareness of emotions and increased the skill of emotion-regulation were able to successfully regulate their arousal, which resulted in better decision performance, reaction time, and attention scores on the decision-making tasks. It is suggested that serious games provide an effective platform validated through the evaluative and playtesting studies, that supports the acquisition of the emotion-regulation skill through the direct (visual) and indirect (gameplay) biofeedback presentation on decision-making tasks.