Research on the characteristics of acrophobia in virtual altitude environment. - Fo Hu; Hong Wang 010; Jichi Chen; Jiale Gong (ISR, 2018)

Electroencephalography based fatigue detection using a novel feature fusion and extreme learning machine. - Jichi Chen; Hong Wang; Chengcheng Hua (Cogn. Syst. Res., 2018)

Novel functional brain network methods based on CNN with an application in proficiency evaluation. - Chengcheng Hua; Hong Wang 010; Jichi Chen; Tao Zhang; Qiaoxiu Wang; Wen-Wen Chang (Neurocomputing, 2019)

Detecting Unfavorable Driving States in Electroencephalography Based on a PCA Sample Entropy Feature and Multiple Classification Algorithms. - Tao Zhang; Hong Wang; Jichi Chen; Enqiu He (Entropy, 2020)

Recognizing drowsiness in young men during real driving based on electroencephalography using an end-to-end deep learning approach. - Jichi Chen; Shjie Wang; Enqiu He; Hong Wang; Lin Wang (Biomed. Signal Process. Control., 2021)

Acrophobia Quantified by EEG Based on CNN Incorporating Granger Causality. - Fo Hu; Hong Wang 010; Qiaoxiu Wang; Naishi Feng; Jichi Chen; Tao Zhang (Int. J. Neural Syst., 2021)

Two-dimensional phase lag index image representation of electroencephalography for automated recognition of driver fatigue using convolutional neural network. - Jichi Chen; Shijie Wang; Enqiu He; Hong Wang; Lin Wang (Expert Syst. Appl., 2022)

Convolutional neural network with transfer learning approach for detection of unfavorable driving state using phase coherence image. - Jichi Chen; Hong Wang; Shjie Wang; Enqiu He; Tao Zhang; Lin Wang (Expert Syst. Appl., 2022)

A novel approach for cross-subject unfavorable driving state detection by cooperation between phase-based functional connectivity and convolutional neural network. - Jichi Chen; Hong Wang; Enqiu He (Biomed. Signal Process. Control., 2023)

A Transfer Learning-Based CNN Deep Learning Model for Unfavorable Driving State Recognition. - Jichi Chen; Hong Wang; Enqiu He (Cogn. Comput., 2024)

Deep learning approach for detection of unfavorable driving state based on multiple phase synchronization between multi-channel EEG signals. - Jichi Chen; Yuguo Cui; Hong Wang; Enqiu He; Adi Alhudhaif (Inf. Sci., 2024)

Advances in EEG-based emotion recognition: Challenges, methodologies, and future directions. - Jichi Chen; Yuguo Cui; Chunfeng Wei; Kemal Polat; Fayadh Alenezi (Appl. Soft Comput., 2025)