Exploring the design of interactive smart textiles for emotion regulation

The present study aims to investigate the design of interactive textiles for emotion regulation. In this work we proposed a design which allows users to visualize their physiological data and help regulate their emotions. We used the Research through Design method to explore how physiological data could be represented in four different interactive textiles and how movement-based interaction could be designed to support users’ understanding and regulation of their emotional state. After an initial user interview evaluation with several textile prototypes, light and vibration were selected as modalities within the biofeedback-based interaction. A smart interactive shawl that reacts to changes in emotional arousal was designed to help the users know their emotion and adjust it, if necessary, with the support of electrodermal activity sensor and pressure-based sensors. The results of the second study showed that the smart shawl could help the user to visualize their emotions and reduce their stress level by interacting with it. © 2020, Springer Nature Switzerland AG

Psychophysiology in games

Psychophysiology is the study of the relationship between psychology and its physiological manifestations. That relationship is of particular importance for both game design and ultimately gameplaying. Players’ psychophysiology offers a gateway towards a better understanding of playing behavior and experience. That knowledge can, in turn, be beneficial for the player as it allows designers to make better games for them; either explicitly by altering the game during play or implicitly during the game design process. This chapter argues for the importance of physiology for the investigation of player affect in games, reviews the current state of the art in sensor technology and outlines the key phases for the application of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject (project no: 318803).peer-reviewe

Biosignals reflect pair-dynamics in collaborative work : EDA and ECG study of pair-programming in a classroom environment

Collaboration is a complex phenomenon, where intersubjective dynamics can greatly affect the productive outcome. Evaluation of collaboration is thus of great interest, and can potentially help achieve better outcomes and performance. However, quantitative measurement of collaboration is difficult, because much of the interaction occurs in the intersubjective space between collaborators. Manual observation and/or self-reports are subjective, laborious, and have a poor temporal resolution. The problem is compounded in natural settings where task-activity and response-compliance cannot be controlled. Physiological signals provide an objective mean to quantify intersubjective rapport (as synchrony), but require novel methods to support broad deployment outside the lab. We studied 28 student dyads during a self-directed classroom pair-programming exercise. Sympathetic and parasympathetic nervous system activation was measured during task performance using electrodermal activity and electrocardiography. Results suggest that (a) we can isolate cognitive processes (mental workload) from confounding environmental effects, and (b) electrodermal signals show role-specific but correlated affective response profiles. We demonstrate the potential for social physiological compliance to quantify pair-work in natural settings, with no experimental manipulation of participants required. Our objective approach has a high temporal resolution, is scalable, non-intrusive, and robust.Peer reviewe

Abandon et clôture des fours de potiers : un geste systématique ?

Analyser les gestes structurés qui reflètent des possibles rites et croyances en contexte artisanal. Est-ce que les potiers gallo-romains installent et clôturent leurs structures artisanales accompagnés de rites particuliers et comment les identifier

A preliminary framework for a social robot “sixth sense”

Building a social robot that is able to interact naturally with people is a challenging task that becomes even more ambitious if the robots’ interlocutors are children involved in crowded scenarios like a classroom or a museum. In such scenarios, the main concern is enabling the robot to track the subjects’ social and affective state modulating its behaviour on the basis of the engagement and the emotional state of its interlocutors. To reach this goal, the robot needs to gather visual and auditory data, but also to acquire physiological signals, which are fundamental for understating the interlocutors’ psycho-physiological state. Following this purpose, several Human-Robot Interaction (HRI) frameworks have been proposed in the last years, although most of them have been based on the use of wearable sensors. However, wearable equipments are not the best technology for acquisition in crowded multi-party environments for obvious reasons (e.g., all the subjects should be prepared before the experiment by wearing the acquisition devices). Furthermore, wearable sensors, also if designed to be minimally intrusive, add an extra factor to the HRI scenarios, introducing a bias in the measurements due to psychological stress. In order to overcome this limitations, in this work, we present an unobtrusive method to acquire both visual and physiological signals from multiple subjects involved in HRI. The system is able to integrate acquired data and associate them with unique subjects’ IDs. The implemented system has been tested with the FACE humanoid in order to assess integrated devices and algorithms technical features. Preliminary tests demonstrated that the developed system can be used for extending the FACE perception capabilities giving it a sort of sixth sense that will improve the robot empathic and behavioural capabilities

“Am I talking to a human or a robot?” : a preliminary study of human’s perception in human-humanoid interaction and its effects in cognitive and emotional states

The current preliminary study concerns the identification of the effects human-humanoid interaction can have on human emotional states and behaviors, through a physical interaction. Thus, we have used three cases where people face three different types of physical interaction with a neutral person, Nadine social robot and the person on which Nadine was modelled, Professor Nadia Thalmann. To support our research, we have used EEG recordings to capture the physiological signals derived from the brain during each interaction, audio recordings to compare speech features and a questionnaire to provide psychometric data that can complement the above. Our results mainly showed the existence of frontal theta oscillations while interacting with the humanoid that probably shows the higher cognitive effort of the participants, as well as differences in the occipital area of the brain and thus, the visual attention mechanisms. The level of concentration and motivation of participants while interacting with the robot were higher indicating also higher amount of interest. The outcome of this experiment can broaden the field of human-robot interaction, leading to more efficient, meaningful and natural human-robot interaction.NRF (Natl Research Foundation, S’pore)Accepted versio