@article {2209, title = {Inference of Human Affective States from Psychophysiological Measurements Extracted under Ecologically Valid Conditions}, journal = {FRONTIERS IN NEUROSCIENCE}, volume = {8}, year = {2014}, abstract = {

Compared to standard laboratory protocols, the measurement of psychophysiological signals in real world experiments poses technical and methodological challenges due to external factors that cannot be directly controlled. To address this problem, we propose a hybrid approach based on an immersive and human accessible space called the eXperience Induction Machine (XIM), that incorporates the advantages of a laboratory within a life-like setting. The XIM integrates unobtrusive wearable sensors for the acquisition of psychophysiological signals suitable for ambulatory emotion research. In this paper, we present results from two different studies conducted to validate the XIM as a general-purpose sensing infrastructure for the study of human affective states under ecologically valid conditions. In the first investigation, we recorded and classified signals from subjects exposed to pictorial stimuli corresponding to a range of arousal levels, while they were free to walk and gesticulate. In the second study, we designed an experiment that follows the classical conditioning paradigm, a well-known procedure in the behavioral sciences, with the additional feature that participants were free to move in the physical space, as opposed to similar studies measuring physiological signals in constrained laboratory settings. Our results indicate that, by using our sensing infrastructure, it is indeed possible to infer human event-elicited affective states through measurements of psychophysiological signals under ecological conditions.

}, doi = {10.3389/fnins.2014.00286}, author = {A. Betella and R. Zucca and Cetnarski, A and A. Greco and A Lanata and D. Mazzei and A. Tognetti and X. D. Arsiwalla and P Omedas and D. De Rossi and Verschure, P} } @conference {2213, title = {Interpreting Psychophysiological States Using Unobtrusive Wearable Sensors in Virtual Reality}, booktitle = {Proc. of The Seventh International Conference on Advances in Computer-Human Interactions}, year = {2014}, abstract = {

One of the main challenges in the study of human be- havior is to quantitatively assess the participants? affective states by measuring their psychophysiological signals in ecologically valid conditions. The quality of the acquired data, in fact, is often poor due to artifacts generated by natural interactions such as full body movements and gestures. We created a technology to address this problem. We enhanced the eXperience Induction Machine (XIM), an immersive space we built to conduct experiments on human behavior, with unobtrusive wearable sensors that measure electrocardiogram, breathing rate and electrodermal response. We conducted an empirical validation where participants wearing these sensors were free to move in the XIM space while exposed to a series of visual stimuli taken from the International Affective Picture System (IAPS). Our main result consists in the quan- titative estimation of the arousal range of the affective stimuli through the analysis of participants? psychophysiological states. Taken together, our findings show that the XIM constitutes a novel tool to study human behavior in life-like conditions.

}, author = {A. Betella and Pacheco, D. and R. Zucca and X. D. Arsiwalla and P Omedas and A Lanata and D. Mazzei and A. Tognetti and A. Greco and N. Carbonaro and Wagner, J. and Lingenfelser, F. and Andr{\`e}, E. and D. De Rossi and Verschure, P.} } @conference {2226, title = {XIM-Engine: a software framework to support the development of interactive applications that uses conscious and unconscious reactions in immersive mixed reality}, booktitle = {VIRTUAL REALITY INTERNATIONAL CONFERENCE}, year = {2014}, abstract = {

The development of systems that allow multimodal interpretation of human-machine interaction is crucial to advance our understanding and validation of theoretical models of user behavior. In particular, a system capable of collecting, perceiving and interpreting unconscious behavior can provide rich contextual information for an interactive system. One possible application for such a system is in the exploration of complex data through immersion, where massive amounts of data are generated every day both by humans and computer processes that digitize information at different scales and resolutions thus exceeding our processing capacity. We need tools that accelerate our understanding and generation of hypotheses over the datasets, guide our searches and prevent data overload. We describe XIM- engine, a bio-inspired software framework designed to capture and analyze multi-modal human behavior in an immersive environment. The framework allows performing studies that can advance our understanding on the use of conscious and unconscious reactions in interactive systems.

}, author = {P. Omedas and A. Betella and Zucca, R. and X. D. Arsiwalla and Pacheco, D. and J. Wagner and F. Lingenfelser and D. Mazzei and A Lanata and A. Tognetti and Goldhoorn, A. and Guerra, E. and Alqu{\`\i}zar, R. and Grau, A. and Sanfeliu, A. and D. De Rossi and E. Andr{\'e} and P. F. M. J. Verschure} } @conference {1812, title = {Advanced Interfaces to Stem the Data Deluge in Mixed Reality: Placing Human (un)consciuosness in the Loop}, booktitle = {ACM SIGGRAPH 2013}, year = {2013}, address = {New York, NY, USA}, keywords = {Bioengineering}, url = {10.1145/2503385.2503460}, author = {A. Betella and E. Mart{\`\i}nez and R. Zucca and X. D. Arsiwalla and P Omedas and S. Wierenga and A. Mura and J. Wagner and F. Lingenfelser and E. Andr{\'e} and D. Mazzei and A. Tognetti and A Lanata and D. De Rossi and P. F. M. J. Verschure} } @conference {1998, title = {A Sensing Architecture for Empathetic Data Systems}, booktitle = {ACM International Conference Proceeding Series}, year = {2013}, month = {7-8 March}, pages = {{\textendash}}, publisher = {ACM Digital Library}, organization = {ACM Digital Library}, doi = {10.1145/2459236.2459253}, url = {http://dx.medra.org/10.1145/2459236.2459253}, author = {J. Wagner and F. Lingenfelser and E. Andr{\'e} and D. Mazzei and A. Tognetti and D. De Rossi and A. Betella and R. Zucca and P Omedas and P. F. M. J. Verschure} }