Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Modeling stress recognition in typical virtual environments

Date

Authors

Sharma, Nandita

Gedeon, Tamas (Tom)

Publisher

IEEE Communications Society

Abstract

Stress is a major problem in our world today motivating objective understanding of how average individuals respond to stress in a typical activities. The main aim for this paper is to determine whether stress can be recognized using individual-independent

Keywords

Keywords: Classification results; Computational model; Consumer devices; Electro-encephalogram (EEG); Physical signal; Physiological signals; Stress classifications; Stress recognition; Electroencephalography; Films; Genetic algorithms; Health care; Neural networks artificial neural networks; EEG; films; genetic algorithms; physical signals; physiological signals; stress recognition; support vector machines

URI

http://hdl.handle.net/1885/66417

Collections

ANU Research Publications

Source

Modeling stress recognition in typical virtual environments

Type

Conference paper

DOI

10.4108/icst.pervasivehealth.2013.252011

Restricted until

2037-12-31

Downloads

File

Description

01_Sharma_Modeling_stress_recognition_in_2013.pdf (1.3 MB)