About us

Blekinge Institute of Technology (BTH) is a broad‐based university of technology with a clear focus on applied IT and sustainable development of industry and society. Engineering, mathematics, and computing science are strongly represented in BTH research. Today, research activities represent one third of the institute's turnover.

The Game Systems and Interaction Research Laboratory (GSIL) is a research laboratory founded at the BTH School of Computing in 2009. GSIL research is based upon the study of design and interaction, human factors and cognitive engineering. GSIL conducts scientific and empirical studies of human/machine system interaction based upon cognitive science, psychophysiology, and ethnographic methods, and undertakes technology-driven innovation in interactive system concepts, mechanics, supporting technologies, development processes and applications. Specific research interests are methodologies for design, game and interaction design, artificial intelligence, cognitive modeling, Computer Supported Cooperative Work (CSCW), robotics and human-robot interaction and new paradigms for information technologies including ubiquitous computing, wearable and mobile technologies, and user adaptive systems.

The PsyIntEC experiment is conducted by the Cognitive and Neural Engineering (CogNeuro) Research Group within GSIL at BTH. The CogNeuro group seeks to combine theories and methods of cognitive and neural sciences with engineering tools and methodologies, in order to improve development processes and the functionality of technology systems on one hand, and to further the understanding of cognitive and neural systems on the other. The CogNeuro group operates a physical research laboratory with facilities for rapid prototyping, psychophysiology (EEG, GSR, EMG, ECG, and Eye Gaze Tracking) and robotics.

What motivates us

Our high level driving reseach question is: What is the extent to which psychophysiological measures can be used to decrease information overload and improve operator effectiveness in human-robot systems? This question is relevant to any situation where human-robot interaction is occurring. However, in the current project we are especially interested in a context where a person is interacting directly with a robot but not controlling its actions in detail, a situation of increased robot autonomy and possibly higher human emotion generated specifically due to the nature of human-robot interaction, rather than the tasks being performed. Hence we are working with the intense HRI context of a joint human-robot work cell where a human and a robot must collaborate to achieve  specific outcomes. A relevant operational outcome could be, for example, assembling a small electromechanical machine.

The underlying theory supporting the exploration of this research question includes the nature of emotions at behavioural, psychological (subjective), neurological and physiological levels, the relationship between emotions and other cognitive processes, and how these can be externally detected, measured and assessed. We are also concerned with the automation of emotional reasoning. This includes the automated interpretation of physiological measures in the form of the generation of  (for example) probabilistic hypotheses representing the meanings of measures in terms of affect states and their underlying generative bases. The outcomes that we are seeking include a better understanding of affects, the measurement of affects, the automation of affective reasoning, and the development of an empirically grounded understanding of the role and usefulness of automated affective measurement and reasoning in human-robot interaction.