PPG and EMG Based Emotion Recognition using Convolutional Neural Network

Min Lee, Ye Cho, Yun Lee, Dong Pae, Myo Lim, Tae Kang

2019

Abstract

Emotion recognition is an essential part of human computer interaction and there are many sources for emotion recognition. In this study, physiological signals, especially electromyogram (EMG) and photoplethysmogram (PPG) are used to detect the emotion. To classify emotions in more detail, the existing method of modeling emotion which represents the emotion as valence and arousal is subdivided by four levels. Convolutional Neural network (CNN) is adopted for feature extraction and emotion classification. We measure the EMG and PPG signals from 30 subjects using selected 32 videos. Our method is evaluated by what we acquired from participants.

Paper Citation

in Harvard Style

Lee M., Cho Y., Lee Y., Pae D., Lim M. and Kang T. (2019). PPG and EMG Based Emotion Recognition using Convolutional Neural Network.In Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-380-3, pages 595-600. DOI: 10.5220/0007797005950600

in Bibtex Style

@conference{icinco19,
author={Min Lee and Ye Cho and Yun Lee and Dong Pae and Myo Lim and Tae Kang},
title={PPG and EMG Based Emotion Recognition using Convolutional Neural Network},
booktitle={Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2019},
pages={595-600},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007797005950600},
isbn={978-989-758-380-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - PPG and EMG Based Emotion Recognition using Convolutional Neural Network
SN - 978-989-758-380-3
AU - Lee M.
AU - Cho Y.
AU - Lee Y.
AU - Pae D.
AU - Lim M.
AU - Kang T.
PY - 2019
SP - 595
EP - 600
DO - 10.5220/0007797005950600