Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection
Identifieur interne : 000529 ( Main/Exploration ); précédent : 000528; suivant : 000530Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection
Auteurs : Dimitris Giakoumis [Grèce] ; Anastasios Drosou [Royaume-Uni] ; Pietro Cipresso [Italie] ; Dimitrios Tzovaras [Grèce] ; George Hassapis [Grèce] ; Andrea Gaggioli [Italie] ; Giuseppe Riva [Italie]Source :
- PLoS ONE [ 1932-6203 ] ; 2012.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
Abstract
This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing.
Url:
DOI: 10.1371/journal.pone.0043571
PubMed: 23028461
PubMed Central: 3446965
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing.</p>
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<author><name sortKey="Troster, G" uniqKey="Troster G">G Troster</name>
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<author><name sortKey="Jones, Mj" uniqKey="Jones M">MJ Jones</name>
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</TEI>
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<li>Italie</li>
<li>Royaume-Uni</li>
</country>
<region><li>Angleterre</li>
<li>Grand Londres</li>
<li>Lombardie</li>
</region>
<settlement><li>Londres</li>
<li>Milan</li>
</settlement>
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<tree><country name="Grèce"><noRegion><name sortKey="Giakoumis, Dimitris" sort="Giakoumis, Dimitris" uniqKey="Giakoumis D" first="Dimitris" last="Giakoumis">Dimitris Giakoumis</name>
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<name sortKey="Giakoumis, Dimitris" sort="Giakoumis, Dimitris" uniqKey="Giakoumis D" first="Dimitris" last="Giakoumis">Dimitris Giakoumis</name>
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<name sortKey="Tzovaras, Dimitrios" sort="Tzovaras, Dimitrios" uniqKey="Tzovaras D" first="Dimitrios" last="Tzovaras">Dimitrios Tzovaras</name>
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<country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Drosou, Anastasios" sort="Drosou, Anastasios" uniqKey="Drosou A" first="Anastasios" last="Drosou">Anastasios Drosou</name>
</region>
</country>
<country name="Italie"><region name="Lombardie"><name sortKey="Cipresso, Pietro" sort="Cipresso, Pietro" uniqKey="Cipresso P" first="Pietro" last="Cipresso">Pietro Cipresso</name>
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<name sortKey="Gaggioli, Andrea" sort="Gaggioli, Andrea" uniqKey="Gaggioli A" first="Andrea" last="Gaggioli">Andrea Gaggioli</name>
<name sortKey="Gaggioli, Andrea" sort="Gaggioli, Andrea" uniqKey="Gaggioli A" first="Andrea" last="Gaggioli">Andrea Gaggioli</name>
<name sortKey="Riva, Giuseppe" sort="Riva, Giuseppe" uniqKey="Riva G" first="Giuseppe" last="Riva">Giuseppe Riva</name>
<name sortKey="Riva, Giuseppe" sort="Riva, Giuseppe" uniqKey="Riva G" first="Giuseppe" last="Riva">Giuseppe Riva</name>
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