Emotion Feature Selection from Physiological Signal Based on BPSO
- 10.2991/iske.2007.130How to use a DOI?
- Feature Selection, Binary Particle Swarm Optimization(BPSO), Physiological Signals, Emotion Recognition.
In emotion recognition, many irrelevant and redundant features will affect recognition results, so feature selection is necessary. Aimed at emotion physiological signal feature selection, this paper proposed with improved discrete binary particle swarm optimization(BPSO) to increase the correct classification rate of emotion state. When recognizing four emotional states with nearest classifier by four physiological signals, the whole correct recognition rate is up to 85%. Experimental results demonstrate that the BPSO is an effective way to emotion physiological signals feature selection.
- © 2007, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Ruiqing Yang AU - Guangyuan Liu PY - 2007/10 DA - 2007/10 TI - Emotion Feature Selection from Physiological Signal Based on BPSO BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 760 EP - 763 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.130 DO - 10.2991/iske.2007.130 ID - Yang2007/10 ER -