@inproceedings{7cf5fe4545af4bce948b4dc84cfd80cf,
title = "EmotionO+: Physiological signals knowledge representation and emotion reasoning model for mental health monitoring",
abstract = "Emotion is an important indicator of depressive conditions. Emotion recognition based on physiological signals such as electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) has gained significant attraction in healthcare domain research. Sharing of physiological signal data related to emotional response between different healthcare systems has the potential to benefit both laboratory-based healthcare research and 'real-world' clinical practice. However, management and distribution of the data presents significant challenges; addressing these challenges requires advanced tools for data representation, mining and integration. In this paper we propose such a tool which contains an ontology model called EmotionO+ and rules set based on EEG, which is obtained by random forest algorithm to predict emotional state. It presents not only an effective method to enable semantic representation of the EEG and fNIRS data, but also an emotion knowledge mining tool. Results using EEG data in the eNTERFACE'06 dataset show an accuracy for our proposed model of 99.11% as compared to 97.8% for competing methods using the C4.5 algorithm. The experimental results demonstrate that the posited approach is potentially usable for early stage prediction and intervention for depressive disorders.",
keywords = "EEG, emotion-reasoning, emotion-recognition, fNIRS, ontology-based modeling, random forest",
author = "Yun Su and Bin Hu and Lixin Xu and Hanshu Cai and Philip Moore and Xiaowei Zhang and Jing Chen",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 ; Conference date: 02-11-2014 Through 05-11-2014",
year = "2014",
month = dec,
day = "29",
doi = "10.1109/BIBM.2014.6999215",
language = "English",
series = "Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "529--535",
editor = "Huiru Zheng and Hu, {Xiaohua Tony} and Daniel Berrar and Yadong Wang and Werner Dubitzky and Jin-Kao Hao and Kwang-Hyun Cho and David Gilbert",
booktitle = "Proceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014",
address = "United States",
}
