Name
Abstract | ||
|---|---|---|
In this paper, we focus our attention on the development of a virtual reality exposure system (VRE) to induce anxiety to phobic people and on a strategy for recognizing it. We describe a short term anxiety detection from blood volume pulse (BVP) measurement, we detail data collection, feature extraction and classification. We propose a model of anxiety detection using support vector machines (SVM) and evaluate it on the collected data. Results show that our model detects anxiety with a good accuracy. This study aims to support the psychologist in social anxiety diagnosis. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.536 | Systems, Man, and Cybernetics |
Keywords | Field | DocType |
short term anxiety detection,support vector machine,phobic people,blood volume pulse,feature extraction,model detects anxiety,short-term anxiety,detail data collection,virtual reality exposure system,anxiety detection,good accuracy,social anxiety diagnosis,virtual reality exposure,virtual reality,support vector machines | Data collection,Virtual reality,Computer science,Support vector machine,Anxiety,Blood volume pulse,Social anxiety,Feature extraction,Speech recognition,Artificial intelligence,Machine learning | Conference |
ISSN | Citations | PageRank |
1062-922X | 1 | 0.36 |
References | Authors | |
4 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wahida Handouzi | 1 | 2 | 0.71 |
| Choubeila Maaoui | 2 | 58 | 6.24 |
| Alain Pruski | 3 | 75 | 9.01 |
| Abdelhak Moussaoui | 4 | 2 | 1.05 |
| Yamina Bendiouis | 5 | 1 | 0.36 |