A wearable system for the affective monitoring of car racing drivers during simulated conditions
| dc.contributor.author | Katsis, C. D. | en |
| dc.contributor.author | Goletsis, Y. | en |
| dc.contributor.author | Rigas, G. | en |
| dc.contributor.author | Fotiadis, D. I. | en |
| dc.date.accessioned | 2015-11-24T17:05:11Z | |
| dc.date.available | 2015-11-24T17:05:11Z | |
| dc.identifier.issn | 0968090X | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11279 | |
| dc.rights | Default Licence | - |
| dc.subject | Wearable devices, Emotion recognition, Car driver affective monitoring, Biosignal processing, C4.5, Tree Augmented Bayesian classifier | en |
| dc.title | A wearable system for the affective monitoring of car racing drivers during simulated conditions | en |
| heal.abstract | A real time, wearable system for remote monitoring of car racing drivers" emotional state is presented. The so-called AUBADE system (standing for AUgmentation system for roBust emotionAl understanding) consists of a wearable device and a centralized unit. The wearable device is responsible to acquire selected biosignals, pre-process them and wirelesses transmit them from the subject-site to the centralized system. The centralized system, which is the main part of the system and carries most of the processing, has a twofold purpose: on the one hand it performs evaluation of the subject" s emotional state and on the other hand it projects a generic 3D face model whereat the facial expression of the subject can be viewed. A two stage classification scheme is used. First a decision tree is implemented in order to classify the subject" s emotional state as high stress, low stress and valence. Then a Tree Augmented NaΓ―ve Bayesian classifier (TAN) is used to classify valence as euphoria and dysphoria. The centralized system has been validated using a dataset obtained from ten subjects in simulated racing conditions. The emotional classes identified are high stress, low stress, dysphoria and euphoria. The overall classification rate achieved using tenfold cross-validation is high. AUBADE constitutes the first system which has the feasibility of remote and real time affective assessment in car racing, providing a useful addition to the existing telemetry systems used in the domain. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | 10.1016/j.trc.2010.09.004 | - |
| heal.journalName | Transportation Research Part C: Emerging Technologies | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2011 | - |
| heal.publisher | Elsevier | en |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Οικονομικών και Κοινωνικών Επιστημών. Τμήμα Οικονομικών Επιστημών | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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