Szczegóły publikacji
Opis bibliograficzny
Classification of physiological data for emotion recognition / Philip Gouverneur, Joanna JAWOREK-KORJAKOWSKA, Lukas Köping, Kimiaki Shirahama, Paweł KŁECZEK, Marcin Grzegorzek // W: Artificial Intelligence and Soft Computing : 16th International Conference : ICAISC 2017 Zakopane, Poland, June 11–15, 2017 : proceedings, Pt. 1 / eds. Leszek Rutkowski, [et al.]. — Switzerland : Springer International Publishing, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; LNAI 10245). — Toż na Dysku Flash. — ISBN: 978-3-319-59062-2; e-ISBN: 978-3-319-59063-9. — S. 619–627. — Bibliogr. s. 627, Abstr.
Autorzy (6)
- Gouverneur Philip
- AGHJaworek-Korjakowska Joanna
- Köping Lukas
- Shirahama Kimiaki
- AGHKłeczek Paweł
- Grzegorzek Marcin
Dane bibliometryczne
| ID BaDAP | 106558 |
|---|---|
| Data dodania do BaDAP | 2017-06-28 |
| DOI | 10.1007/978-3-319-59063-9_55 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | 16th International Conference on Artificial Intelligence and Soft Computing |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Emotion recognition is seen to be important not only for computer science or sport activity but also for old and sick people to live independently in their own homes as long as possible. In this paper Empatica E4 wristband is used to collect the date and assess the stress level of the user. We describe an algorithm for the classification of physiological data for emotion recognition. The algorithm has been divided into the following steps: data acquisition, signal preprocessing, feature extraction, and classification. The data acquired during various daily activities consist of more than 3 h of wristband signal. Through various stress tests we achieve a maximum accuracy of 71% for a stressed/relaxed classification. These results lead to the conclusion that Empatica E4 wristband can be used as a device for emotion recognition.