EEG-based IQ pattern analysis: considerations on filter design and power ratio equations / Najwa Ahmad Suhaimi ...[et al.]
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 limita...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
UiTM Press
2022
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/63170/1/63170.pdf https://doi.org/10.24191/jeesr.v20i1.007 https://ir.uitm.edu.my/id/eprint/63170/ https://jeesr.uitm.edu.my/v1/ https://doi.org/10.24191/jeesr.v20i1.007 |
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| Institution: | Universiti Teknologi Mara |
| Language: | English |
| Summary: | 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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