通过基于复杂性的脑电图信号分析,分析大脑活动在休息和多任务工作负荷之间的变化

Fractals Pub Date : 2023-11-18 DOI:10.1142/s0218348x23501360
Sriram Parthasarathy, Petra Maresová, K. Rajagopal, H. Namazi
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引用次数: 0

摘要

分析大脑活动在休息和各种条件下的变化是一个重要的研究领域。我们通过量化脑电信号的复杂性,研究了休息和多任务工作负荷(SIMKAP 多任务测试)之间大脑活动的变化。结果表明,在 SIMKAP 多任务测试中,脑电信号的分形维数、样本熵和近似熵均小于休息时。因此,在 SIMKAP 多任务测试中,脑电信号的复杂度低于其他测试。在进一步的研究中,我们可以研究其他条件下大脑活动的变化,这对解码各种条件下的大脑活动大有裨益。
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ANALYSIS OF THE CHANGES IN THE BRAIN ACTIVITY BETWEEN REST AND MULTITASKING WORKLOAD BY COMPLEXITY-BASED ANALYSIS OF EEG SIGNALS
Analysis of the changes in brain activity between rest and various conditions is an important area of research. We investigated the changes in brain activity among rest and multitask workload (SIMKAP multitasking test) by quantifying the complexity of EEG signals. The results showed that EEG signals have smaller fractal dimensions, sample entropy, and approximate entropy during the SIMKAP multitasking test than the rest. Therefore, the complexity of EEG signals was lower during the SIMKAP multitasking test than the rest. In further research, we can study the changes in brain activity among other conditions, which has great benefits in decoding brain activity in various conditions.
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