EEG-based Evaluation of Mental Fatigue Using Machine Learning Algorithms

Author:

Liu Yisi1,Lan Zirui1,Khoo Han Hua Glenn2,Li King Ho Holden2,Sourina Olga1,Mueller-Wittig Wolfgang1

Affiliation:

1. Fraunhofer Singapore, Singapore, Singapore

2. Nanyang Technol. Univ., Singapore, Singapore

Publisher

IEEE

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. EEG-CogNet: A deep learning framework for cognitive state assessment using EEG brain connectivity;Biomedical Signal Processing and Control;2024-12

2. Online Assessment of Spontaneous Mental Fatigue in Construction Workers Considering Data Quality: Improved Online Sequential Extreme Learning Machine;Journal of Construction Engineering and Management;2024-11

3. Artificial intelligence modelling human mental fatigue: A comprehensive survey;Neurocomputing;2024-01

4. EEG Channels Selection Based on BiLSTM and NSGAII;Communications in Computer and Information Science;2024

5. Interweaving Artificial Intelligence and Bio-Signals in Mental Fatigue: Unveiling Dynamics and Future Pathways;2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP);2023-12-15

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