基于脑电图的IQ模式分析:对滤波器设计和功率比方程的考虑

Najwa Ahmad Suhaimi, A. I. Mohd Yassin, M. S. A. Megat Ali, A. H. Jahidin
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摘要

摘要:智力被定义为学习、推理和解决问题的心理能力。最近,研究已经从静止脑电波中描述了不同水平的智商。各种各样的滤波器设计和功率比方程已经提出,都有其独特的优势和局限性。因此,利用已建立的脑电图数据库对预处理算法进行规范化还需要进一步的研究。本研究评估了先前建立的汉明滤波器和等纹滤波器设计。后者在将脑电图过滤成各自的脑电波方面更为优越。尽管有限制,低阶汉明滤波器仍然被推荐,因为所需的内存仅为高阶等纹滤波器的6%。这大大提高了计算效率。互相关函数测试进一步揭示了滤波器设计对产生的脑电波的影响。因此,成功地建立了一套新的功率比方程,用于数据集验证。
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EEG-based IQ Pattern Analysis: Considerations on Filter Design and Power Ratio Equations
51 Abstract—Intelligence is defined as the mental ability to learn, reason and solve problems. Recently, studies have characterized the different levels of intelligence quotient from the resting brainwaves. Various filter designs and power ratio equations have been proposed, all with unique strengths and limitations. Hence, further investigation is required to standardize the pre-processing algorithm using the established electroencephalogram database. The previously established Hamming and equiripple filter designs are evaluated in this study. The later are more superior for filtering the electroencephalogram into the respective brainwaves. Despite the limitations, the low-order Hamming filters are still recommended as the memory required is only 6% of the highorder equiripple filters. These greatly enhance the computational efficiency. The cross-correlation function tests further revealed the impact of filter designs on the resultant brainwaves. Hence, a new set of power ratio equations have been successfully formulated for dataset validation.
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