• Opto-Electronic Engineering
  • Vol. 48, Issue 2, 200013 (2021)
Dong Yindong1、2、*, Ren Fuji1、2、3, and Li Chunbin1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.12086/oee.2021.200013 Cite this Article
    Dong Yindong, Ren Fuji, Li Chunbin. EEG emotion recognition based on linear kernel PCA and XGBoost[J]. Opto-Electronic Engineering, 2021, 48(2): 200013 Copy Citation Text show less
    References

    [1] Vilar P. Designing the user interface: strategies for effective human-computer interaction (5th edition)[J]. J Assoc Inf Sci Technol, 2010, 65(5): 1073–1074.

    [2] Andreasson R, Alenljung B, Billing E, et al. Affective touch in human–robot interaction: conveying emotion to the Nao ro-bot[J]. Int J Soc Robot, 2018, 10(3): 473–491.

    [4] Fragopanagos N, Taylor J G. Emotion recognition in human-computer interaction[J]. Neural Netw, 2005, 18(4): 389–405.

    [6] Ren F J, Huang Z. Automatic facial expression learning method based on humanoid robot XIN-REN[J]. IEEE Trans Hum Mach Syst, 2016, 46(6): 810–821.

    [8] Piana S, Staglianò A, Odone F, et al. Adaptive body gesture representation for automatic emotion recognition[J]. ACM Trans Interact Intell Syst, 2016, 6(1): 6.

    [10] Ren F J, Wang L. Sentiment analysis of text based on three-way decisions[J]. J Intell Fuzzy Syst, 2017, 33(1): 245–254.

    [12] Petrantonakis P C, Hadjileontiadis L J. Adaptive emotional information retrieval from EEG signals in the time-frequency domain[J]. IEEE Trans Signal Process, 2012, 60(5): 2604–2616.

    [13] Lin Y P, Wang C H, Jung T P, et al. EEG-based emotion recognition in music listening[J]. IEEE Trans Biomed Eng, 2010, 57(7): 1798–1806.

    [14] Yin Z, Wang Y X, Liu L, et al. Cross-subject EEG feature selection for emotion recognition using transfer recursive feature elimination[J]. Front Neurorobot, 2017, 11: 19.

    [15] Jenke R, Peer A, Buss M. Feature extraction and selection for emotion recognition from EEG[J]. IEEE Trans Affect Comput, 2014, 5(3): 327–339.

    [16] Li X, Song D W, Zhang P, et al. Exploring EEG features in cross-subject emotion recognition[J]. Front Neurosci, 2018, 12: 162.

    [19] Zheng W L, Zhu J Y, Lu B L. Identifying stable patterns over time for emotion recognition from EEG[J]. IEEE Trans Affect Comput, 2019, 10(3): 417–429.

    [22] Chen J X, Zhang P W, Mao Z J, et al. Accurate EEG-based emotion recognition on combined features using deep convolutional neural networks[J]. IEEE Access, 2019, 7: 44317–44328.

    [24] Atkinson J, Campos D. Improving BCI-based emotion recognition by combining EEG feature selection and kernel classifiers[J]. Expert Syst Appl, 2016, 47: 35–41.

    [25] Gupta R, Laghari K U R, Falk T H. Relevance vector classifier decision fusion and EEG graph-theoretic features for au-tomatic affective state characterization[J]. Neurocomputing, 2016, 174: 875–884.

    [26] Chen T Q, Guestrin C. XGBoost: a scalable tree boosting system[C]//Proceedings of the 22nd ACM SIGKDD International conference on Knowledge Discovery and Data Mining, 2016: 785–794.

    [28] Zheng H T, Yuan J B, Chen L. Short-term load forecasting using EMD-LSTM neural networks with a XGBoost algorithm for feature importance evaluation[J]. Energies, 2017, 10(8): 1168.

    [29] Chakraborty D, Elzarka H. Advanced machine learning techniques for building performance simulation: a comparative analysis[J]. J Build Perform Simul, 2019, 12(2): 193–207.

    [30] Luo Y N, Zou J, Yao C F, et al. HSI-CNN: a novel convolution neural network for hyperspectral image[C]//2018 International Conference on Audio, Language and Image Processing (ICALIP), 2018.

    [31] Ayumi V. Pose-based human action recognition with Extreme Gradient Boosting[C]//2016 IEEE Student Conference on Research and Development (SCOReD), 2016.

    [32] Zhong J C, Sun Y S, Peng W, et al. XGBFEMF: an XGBoost-based framework for essential protein prediction[J]. IEEE Trans NanoBioscience, 2018, 17(3): 243–250.

    [33] Koelstra S, Muhl C, Soleymani M, et al. DEAP: a database for emotion analysis; using physiological signals[J]. IEEE Trans Affect Comput, 2012, 3(1): 18–31.

    Dong Yindong, Ren Fuji, Li Chunbin. EEG emotion recognition based on linear kernel PCA and XGBoost[J]. Opto-Electronic Engineering, 2021, 48(2): 200013
    Download Citation