Abstract
In this paper, Granger causality (GC) and New causality (NC) analysis methods are applied in frequency domain to reveal causality changes from non-fatigue state to fatigue state with EEG signals during video game-playing. EEG signals were recorded while a subject was playing video-games. Results show that fatiguing phenomenon was observed in 15 subjects using NC in [20, 30] Hz while only 13 subjects were identified with GC for comparison. The NC further showed the bi-directional causality changes between the two hemispheres during unilateral forearm movements. We noticed that half of the subjects had predominant active hemisphere while the other half showed the opposite, especially to the ones with higher fatigue level. The findings demonstrate that the NC method is better than the GC to reveal causal influence between homologous motor areas of active and inactive hemispheres in this study.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61473110 and Grant 61633010, in part by the International Science and Technology Cooperation Program of China under Grant 2014DFG12570, and in part by the U.S. National Science Foundation under Grant 1156639 and Grant 1229213.
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Zhu, Y. et al. (2017). Identify Non-fatigue State to Fatigue State Using Causality Measure During Game Play. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10637. Springer, Cham. https://doi.org/10.1007/978-3-319-70093-9_61
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DOI: https://doi.org/10.1007/978-3-319-70093-9_61
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