Publication detail

Stress detection on non-EEG physiolog. data

JINDRA, J. NĚMCOVÁ, A.

Original Title

Stress detection on non-EEG physiolog. data

English Title

Stress detection on non-EEG physiolog. data

Type

conference paper

Language

Czech

Original Abstract

Stress detection based on Non-EEG physiological data can be usefulfor monitoring dri-vers, pilots, workers,and other subjects, where standard EEG monitoring is unsuitable. This work usesNon-EEG database freelyavailable fromPhysionet. The database contains recordsof heart ra-te, saturation of blood oxygen, motion, a conductance of skin and temperature. Model for automatic detection of stress was learned on these data. Best results were reached using a model of a decision tree with25 features. The accuracy of the resulting model is approximately 93 %.

English abstract

Stress detection based on Non-EEG physiological data can be usefulfor monitoring dri-vers, pilots, workers,and other subjects, where standard EEG monitoring is unsuitable. This work usesNon-EEG database freelyavailable fromPhysionet. The database contains recordsof heart ra-te, saturation of blood oxygen, motion, a conductance of skin and temperature. Model for automatic detection of stress was learned on these data. Best results were reached using a model of a decision tree with25 features. The accuracy of the resulting model is approximately 93 %.

Keywords

Stress, detection, physiological signals, Non–EEG detection, artificial intelligence,machine learning,decision trees

Key words in English

Stress, detection, physiological signals, Non–EEG detection, artificial intelligence,machine learning,decision trees

Authors

JINDRA, J.; NĚMCOVÁ, A.

Released

25. 4. 2019

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Location

Brno

ISBN

978-80-214-5735-5

Book

Proceedings of the 25th Conference STUDENT EEICT 2019

Pages from

203

Pages to

206

Pages count

4

URL

BibTex

@inproceedings{BUT156802,
  author="Jakub {Jindra} and Andrea {Němcová}",
  title="Stress detection on non-EEG physiolog. data",
  booktitle="Proceedings of the 25th Conference STUDENT EEICT 2019",
  year="2019",
  pages="203--206",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií",
  address="Brno",
  isbn="978-80-214-5735-5",
  url="http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2019_sbornik.pdf"
}