Title :
Extraction of facial features as indicators of stress and anxiety
Author :
M. Pediaditis;G. Giannakakis;F. Chiarugi;D. Manousos;A. Pampouchidou;E. Christinaki;G. Iatraki;E. Kazantzaki;P. G. Simos;K. Marias;M. Tsiknakis
Author_Institution :
Foundation for Research and Technology - Hellas, Institute of Computer Science, Computational BioMedicine Laboratory, Vassilika Vouton, 71110, Heraklion, Crete, Greece
Abstract :
Stress and anxiety heavily affect the human wellbeing and health. Under chronic stress, the human body and mind suffers by constantly mobilizing all of its resources for defense. Such a stress response can also be caused by anxiety. Moreover, excessive worrying and high anxiety can lead to depression and even suicidal thoughts. The typical tools for assessing these psycho-somatic states are questionnaires, but due to their shortcomings, by being subjective and prone to bias, new more robust methods based on facial expression analysis have emerged. Going beyond the typical detection of 6 basic emotions, this study aims to elaborate a set of facial features for the detection of stress and/or anxiety. It employs multiple methods that target each facial region individually. The features are selected and the classification performance is measured based on a dataset consisting 23 subjects. The results showed that with feature sets of 9 and 10 features an overall accuracy of 73% is reached.
Keywords :
"Stress","Mouth","Feature extraction","Psychology","Heart rate","Face","Accuracy"
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
Electronic_ISBN :
1558-4615
DOI :
10.1109/EMBC.2015.7319199