Shourie Nasrin
Faculty of Technology and Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
J Med Signals Sens. 2016 Oct-Dec;6(4):203-217.
In this article, multichannel electroencephalogram (EEG) signals of artists and nonartists were analyzed during the performances of visual perception and mental imagery of paintings using cepstrum coefficients. Each of the calculated cepstrum coefficients and their parameters such as energy, average, standard deviation and entropy were separately used for distinguishing the two groups. It was found that a distinguishing coefficient might exist among the cepstrum coefficients, which could separate the two groups despite electrode placement. It was also observed that the two groups were distinguishable during the three states using the cepstrum coefficient parameters. However, separating the two groups was dependent on channel selection in this regard. The cepstrum coefficient parameters were found significantly lower for artists as compared to nonartists during the visual perception and the mental imagery, indicating a decreased average energy of EEG for artists. In addition, a similar significant decreasing trend in the cepstrum coefficient parameters was observed from occipital to frontal brain regions during the performances of the two cognitive tasks for the two groups, suggesting that visual perception and its mental imagery overlap in neuronal resources. The two groups were also classified using a neural gas classifier and a support vector machine classifier. The obtained average classification accuracies during the visual perception, the mental imagery, and at rest in the case of using the best selected distinguishable cepstrum coefficients were 76.87%, 77.5%, and 97.5%, respectively; however, a decrease in average recognition accuracy was found for classifying the two groups using the cepstrum coefficient parameters.
在本文中，运用倒谱系数对艺术家和非艺术家在绘画视觉感知与心理意象表现过程中的多通道脑电图（EEG）信号进行了分析。计算得到的每个倒谱系数及其诸如能量、平均值、标准差和熵等参数被分别用于区分这两组人群。研究发现，在倒谱系数中可能存在一个区分系数，该系数能够区分这两组人群，而不受电极位置的影响。还观察到，利用倒谱系数参数，在三种状态下这两组人群是可区分的。然而，在这方面，区分这两组人群依赖于通道选择。在视觉感知和心理意象过程中，艺术家的倒谱系数参数显著低于非艺术家，这表明艺术家的脑电图平均能量有所下降。此外，在两组人群进行两项认知任务表现时，从枕叶到额叶脑区，倒谱系数参数呈现出类似的显著下降趋势，这表明视觉感知及其心理意象在神经资源上存在重叠。还使用神经气体分类器和支持向量机分类器对这两组人群进行了分类。在使用最佳选择的可区分倒谱系数的情况下，视觉感知、心理意象以及静息状态下获得的平均分类准确率分别为76.87%、77.5%和97.5%；然而，使用倒谱系数参数对两组人群进行分类时，平均识别准确率有所下降。
