@article {2717,
	title = {Neuro-fuzzy physiological computing to assess stress levels in virtual reality therapy},
	journal = {INTERACTING WITH COMPUTERS},
	volume = {27},
	year = {2015},
	pages = {521{\textendash}533},
	keywords = {Bioengineering},
	issn = {0953-5438},
	doi = {10.1093/iwc/iwv010},
	url = {http://dx.medra.org/10.1093/iwc/iwv010},
	author = {Tartarisco, G. and N. Carbonaro and A. Tonacci and G. M. Bernava and A. Arnao and G. Crifaci and P. Cipresso and G. Riva and A. Gaggioli and D. De Rossi and A. Tognetti and G. Pioggia}
}
@article {2228,
	title = {A Decision Support System for Real-Time Stress Detection During Virtual Reality Exposure},
	year = {2014},
	pages = {114{\textendash}120},
	abstract = {<p>Virtual Reality (VR) is increasingly being used in combination with psycho-physiological measures to improve assessment of distress in mental health research and therapy. However, the analysis and interpretation of multiple physiological measures is time consuming and requires specific skills, which are not available to most clinicians. To address this issue, we designed and developed a Decision Support System (DSS) for automatic classification of stress levels during exposure to VR environments. The DSS integrates different biosensor data (ECG, breathing rate, EEG) and behavioral data (body gestures correlated with stress), following a training process in which self-rated and clinical-rated stress levels are used as ground truth. Detected stress events for each VR session are reported to the therapist as an aggregated value (ranging from 0 to 1) and graphically displayed on a diagram accessible by the therapist through a web-based interface.</p>
},
	doi = {10.3233/978-1-61499-375-9-114},
	author = {A. Gaggioli and P. Cipresso and Serino, S. and G. Pioggia and Tartarisco, G. and Baldus, G. and Corda, D. and M. Ferro and N. Carbonaro and A. Tognetti and D. De Rossi and Giakoumis, D. and Tzovaras, D. and Riera, A. and G. Riva}
}
@conference {1814,
	title = {A Mobile Biosensor to detect Cardiorespiratory Activity for Stress Tracking},
	booktitle = {IEEE  7th International Conference on  Pervasive Computing Technologies for Healthcare (PervasiveHealth)},
	year = {2013},
	pages = {440 - 445 },
	address = {Venice, Italy},
	abstract = {<p style="text-align: justify;">Stress is an increasingly recognized phenomenon that has negative effects on growing numbers of people. Stress assessment is a complex issue, but different studies have shown that monitoring user psychophysiological parameter during daily life can be greatly helpful in stress evaluation. In this study a wearable biosensor platform able to collect physiological and behavioral parameters is reported. The developed wearable platform, in terms of hardware and processing algorithms, is described. Moreover the use of this wearable biosensor platform in combination with advanced simulation technologies, such as virtual reality offer interesting opportunities for innovative personal health-care solutions to stress. A recently founded European project, "INTERSTRESS - Interreality in the management and treatment of stress-related disorders," will take into account these relevant aspects.</p>
},
	keywords = {Bioengineering},
	issn = {978-1-4799-0296-5 },
	author = {N. Carbonaro and A. Tognetti and G. Anania and D. De Rossi and P. Cipresso and A. Gaggioli and G. Riva}
}
@conference {2024,
	title = {Interreality: The use of advanced technologies in the assessment and treatement of psychological stress},
	booktitle = {Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications ISDA{\textquoteright}10},
	year = {2010},
	month = {29 Nov- 1 Dec},
	pages = {1047{\textendash}1051},
	doi = {10.1109/ISDA.2010.5687047},
	url = {http://dx.medra.org/10.1109/ISDA.2010.5687047},
	author = {G. Pioggia and N. Carbonaro and G. Anania and A. Tognetti and Tartarisco, G. and M. Ferro and D. De Rossi and G. Riva}
}
