Emotional quality level recognition based on HRV

研究成果: Conference contribution

3 引文 斯高帕斯(Scopus)

摘要

This paper explores the detection of emotional levels, high, medium and low from ECG signals. Features of ECG are extracted from frequency domain, time domain and nonlinear method and normalized by z-score method. Then SFS feature selection is applied followed by LDA feature transformation. After that, the transformed features are applied to KNNR classifier. According to our results, it was found that subjects of different characteristics reveal different biosignal responses. While subjects are regarded as optimistic characteristics, they have higher responses on positive films. On the other hand, the pessimistic subjects have higher responses on negative films. When classifiers are established separately for optimistic and pessimistic subjects, we can achieve the recognition rate of 97.8%, where 7 features are selected, and 94.0%, where 8 features are selected, for optimistic and pessimistic groups respectively. When the classification is built from all the subjects, the recognition rate is reduced slightly, but it can still maintain a recognition rate of 90.4%.

原文English
主出版物標題2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
DOIs
出版狀態Published - 2010 十二月 1
事件2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain
持續時間: 2010 七月 182010 七月 23

出版系列

名字Proceedings of the International Joint Conference on Neural Networks

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
國家Spain
城市Barcelona
期間10-07-1810-07-23

    指紋

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

引用此

Wu, M. H., Wang, C. J., Yang, Y. K., Wang, J. S., & Chung, P. C. (2010). Emotional quality level recognition based on HRV. 於 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 [5596543] (Proceedings of the International Joint Conference on Neural Networks). https://doi.org/10.1109/IJCNN.2010.5596543