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.
A decision support system for real-time stress detection during virtual reality exposure.
Pioggia Giovanni;Tartarisco Gennaro;Ferro Marcello;
2014
Abstract
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.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di Fisiologia Clinica - IFC | - |
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Gaggioli Andrea | it |
| dc.authority.people | Cipresso Pietro | it |
| dc.authority.people | Serino Silvia | it |
| dc.authority.people | Pioggia Giovanni | it |
| dc.authority.people | Tartarisco Gennaro | it |
| dc.authority.people | Baldus Giovanni | it |
| dc.authority.people | Corda Daniele | it |
| dc.authority.people | Ferro Marcello | it |
| dc.authority.people | Carbonaro Nicola | it |
| dc.authority.people | Tognetti Alessandro | it |
| dc.authority.people | De Rossi Danilo | it |
| dc.authority.people | Giakoumis Dimitris | it |
| dc.authority.people | Tzovaras Dimitrios | it |
| dc.authority.people | Riera Alejandro | it |
| dc.authority.people | Riva Giuseppe | it |
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| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza | Istituto per la Ricerca e l'Innovazione Biomedica -IRIB | * |
| dc.contributor.appartenenza.mi | 918 | * |
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| dc.date.accessioned | 2024/02/17 21:50:10 | - |
| dc.date.available | 2024/02/17 21:50:10 | - |
| dc.date.issued | 2014 | - |
| dc.description.abstracteng | 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. | - |
| dc.description.affiliations | ATN-P Lab., Istituto Auxologico Italiano, Milan, Italy; ATN-P Lab., Istituto Auxologico Italiano, Milan, Italy; ATN-P Lab., Istituto Auxologico Italiano, Milan, Italy; IFC-CNR, Pisa; IFC-CNR, Pisa; IFC-CNR, Pisa; IFC-CNR, Pisa; ILC-CNR, Pisa; Research Center E.Piaggio, University of Pisa, Italy; Research Center E.Piaggio, University of Pisa, Italy; Research Center E.Piaggio, University of Pisa, Italy; Informatics and Telematics Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thermi, Thessaloniki, Greece; Informatics and Telematics Institute, Centre for Research and Technology Hellas (CERTH-ITI), Thermi, Thessaloniki, Greece; Starlab Barcelona SL, Barcelona, Spain; ATN-P Lab., Istituto Auxologico Italiano, Milan, Italy | - |
| dc.description.allpeople | Gaggioli, Andrea; Cipresso, Pietro; Serino, Silvia; Pioggia, Giovanni; Tartarisco, Gennaro; Baldus, Giovanni; Corda, Daniele; Ferro, Marcello; Carbonaro, Nicola; Tognetti, Alessandro; De Rossi, Danilo; Giakoumis, Dimitris; Tzovaras, Dimitrios; Riera, Alejandro; Riva, Giuseppe | - |
| dc.description.allpeopleoriginal | Gaggioli, Andrea; Cipresso, Pietro; Serino, Silvia; Pioggia, Giovanni; Tartarisco, Gennaro; Baldus, Giovanni; Corda, Daniele; Ferro, Marcello; Carbonaro, Nicola; Tognetti, Alessandro; De Rossi, Danilo; Giakoumis, Dimitris; Tzovaras, Dimitrios; Riera, Alejandro; Riva, Giuseppe | - |
| dc.description.fulltext | restricted | en |
| dc.description.numberofauthors | 15 | - |
| dc.identifier.doi | 10.3233/978-1-61499-375-9-114 | - |
| dc.identifier.isi | WOS:24732491 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/256842 | - |
| dc.language.iso | eng | - |
| dc.miur.last.status.update | 2024-07-15T10:55:01Z | * |
| dc.relation.alleditors | J.D. Westwood | - |
| dc.relation.conferencename | Medicine Meets Virtual Reality (MMVR21) | - |
| dc.relation.firstpage | 114 | - |
| dc.relation.ispartofbook | Medicine Meets Virtual Reality | - |
| dc.relation.lastpage | 120 | - |
| dc.relation.volume | 196 | - |
| dc.subject.keywords | Psychological Stress | - |
| dc.subject.keywords | Psychophysiology | - |
| dc.subject.keywords | Virtual Reality | - |
| dc.subject.keywords | Decision Support System | - |
| dc.subject.keywords | Biosensors. | - |
| dc.subject.singlekeyword | Psychological Stress | * |
| dc.subject.singlekeyword | Psychophysiology | * |
| dc.subject.singlekeyword | Virtual Reality | * |
| dc.subject.singlekeyword | Decision Support System | * |
| dc.subject.singlekeyword | Biosensors | * |
| dc.title | A decision support system for real-time stress detection during virtual reality exposure. | en |
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| iris.scopus.extIssued | 2014 | - |
| iris.scopus.extTitle | A decision support system for real-time stress detection during virtual reality exposure | - |
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