@INPROCEEDINGS{6681548,
author={Heger, D. and Mutter, R. and Herff, C. and Putze, F. and Schultz, T.},
booktitle={Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on},
title={Continuous Recognition of Affective States by Functional Near Infrared Spectroscopy Signals},
year={2013},
pages={832-837},
abstract={Functional near infrared spectroscopy (fNIRS) is becoming more and more popular as an innovative imaging modality for brain computer interfaces. A continuous (i.e. asynchronous) affective state monitoring system using fNIRS signals would be highly relevant for numerous disciplines, including adaptive user interfaces, entertainment, biofeedback, and medical applications. However, only stimulus-locked emotion recognition systems have been proposed by now. fNRIS signals of eight subjects at eight prefrontal locations have been recorded in response to three different classes of affect induction by emotional audio-visual stimuli and a neutral class. Our system evaluates short windows of five seconds length to continuously recognize affective states. We analyze hemodynamic responses, present a careful evaluation of binary classification tasks and investigate classification accuracies over the time.},
keywords={audio-visual systems;haemodynamics;infrared spectra;pattern classification;physiology;psychology;signal classification;adaptive user interfaces;affect induction;asynchronous affective state monitoring system;binary classification task accuracies;biofeedback application;brain computer interface;continuous affective state recognition;emotional audio-visual stimuli;entertainment application;fNRIS signal recording;functional near infrared spectroscopy signals;hemodynamic response analysis;imaging modality;medical application;neutral class;prefrontal locations;short-window evaluation;stimulus-locked emotion recognition systems;Accuracy;Detectors;Emotion recognition;Feature extraction;Hemodynamics;Monitoring;Training data;affective states;asynchronous;continuous recognition;emotion recognition;fNIRS;functional Near Infrared Spectroscopy},
url={https://www.csl.uni-bremen.de/cms/images/documents/publications/acii13_paper.pdf},
doi={10.1109/ACII.2013.156},
ISSN={2156-8103},
month={Sept},}