%0 Journal Article %J Cell biochemistry and biophysics %D 2014 %T Characterization of 3-Iodothyronamine In Vitro Dynamics by Mathematical Modeling %A G. Orsi %A Ghelardoni, S. %A Saba, A. %A R. Zucca %A G. Vozzi %B Cell biochemistry and biophysics %V 68 %P 37–47 %G eng %0 Journal Article %J FRONTIERS IN NEUROSCIENCE %D 2014 %T Inference of Human Affective States from Psychophysiological Measurements Extracted under Ecologically Valid Conditions %A A. Betella %A R. Zucca %A Cetnarski, A %A A. Greco %A A Lanata %A D. Mazzei %A A. Tognetti %A X. D. Arsiwalla %A P Omedas %A D. De Rossi %A Verschure, P %X

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.

%B FRONTIERS IN NEUROSCIENCE %V 8 %G eng %R 10.3389/fnins.2014.00286 %0 Conference Paper %B Proc. of The Seventh International Conference on Advances in Computer-Human Interactions %D 2014 %T Interpreting Psychophysiological States Using Unobtrusive Wearable Sensors in Virtual Reality %A A. Betella %A Pacheco, D. %A R. Zucca %A X. D. Arsiwalla %A P Omedas %A A Lanata %A D. Mazzei %A A. Tognetti %A A. Greco %A N. Carbonaro %A Wagner, J. %A Lingenfelser, F. %A Andrè, E. %A D. De Rossi %A Verschure, P. %X

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.

%B Proc. of The Seventh International Conference on Advances in Computer-Human Interactions %0 Conference Paper %B ACM SIGGRAPH 2013 %D 2013 %T Advanced Interfaces to Stem the Data Deluge in Mixed Reality: Placing Human (un)consciuosness in the Loop %A A. Betella %A E. Martìnez %A R. Zucca %A X. D. Arsiwalla %A P Omedas %A S. Wierenga %A A. Mura %A J. Wagner %A F. Lingenfelser %A E. André %A D. Mazzei %A A. Tognetti %A A Lanata %A D. De Rossi %A P. F. M. J. Verschure %K Bioengineering %B ACM SIGGRAPH 2013 %C New York, NY, USA %U 10.1145/2503385.2503460 %0 Journal Article %J Cell Biochem Biophys %D 2013 %T Characterization of 3-Iodothyronamine In Vitro Dynamics by Mathematical Modeling %A G. Orsi %A S. Ghelardoni %A A. Saba %A R. Zucca %A G. Vozzi %K Bioengineering %B Cell Biochem Biophys %G eng %R 10.1007/s12013-013-9680-y %0 Conference Paper %B ACM International Conference Proceeding Series %D 2013 %T A Sensing Architecture for Empathetic Data Systems %A J. Wagner %A F. Lingenfelser %A E. André %A D. Mazzei %A A. Tognetti %A D. De Rossi %A A. Betella %A R. Zucca %A P Omedas %A P. F. M. J. Verschure %B ACM International Conference Proceeding Series %I ACM Digital Library %P – %8 7-8 March %U http://dx.medra.org/10.1145/2459236.2459253 %R 10.1145/2459236.2459253 %0 Journal Article %J IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING %D 2011 %T LTI Models for 3-Iodothyronamine Time Dynamics: A Multiscale View. %A G. Orsi %A Frascarelli, S %A R. Zucca %A G. Vozzi %K Bioengineering %B IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING %V 58 %P 3153 - 3157 %G eng