Reactions of Brain in English Reading Tests

Writing is a survival skill in schools and many children are reported to have suffered from writing disorder. Emerging technology enables this disorder detectable through monitoring of EEG signals. However, in working with EEG, the lack of methodological approach would lead to gargantuan of data and thus wastage in resources and time. Furthermore, placing of a large number of electrodes on the recording cap will cause discomfort to the subject, with data being more liable to false readings and artifacts. Recognizing the number of electrodes through proper localization plays a fundamental role in improving the overall performance of an EEG acquisition system, thus the objective of this research. This study involves the following phases: Data Collection, Data Acquisition and Data Analysis. Target population are normal and healthy subjects of age between 18 and 25. The EEG signals are recorded with electrodes at activation areas along the documented signal pathway of the brain (C3, C4, P3, P4, O1, O2, T7, FC5) during reading and writing. Fast Fourier Transform (FFT) is applied to transform the EEG in time domain into frequency domain so that signature features in frequency content during relaxation and sentence writing can be extracted. Results showed that relaxation drew on one dominant peak and the frequency content resides in the alpha sub-band while writing activity drew on two dominant peaks, one in alpha and the other in beta sub-band. The frequency range of EEG recorded during relaxation is 8-13 Hz while that during writing is 13-29 Hz, well within the alpha and beta sub-band for the different neuro-activity accordingly. Hence, it can be concluded from experimental results and findings from previous works that electrodes C3/C4, P3/P4, O1/O2, T7 and FC5 are suitable as optimal localized EEG electrode placement for neuro-pathway for reading-writing.

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Reactions of Brain in English Reading Tests

Cited by 2 publications

References 27 publications

English ability score prediction algorithm based on prefrontal cortex blood volume utilizing a regulated linear regression model

English ability score prediction algorithm based on prefrontal cortex blood volume utilizing a regulated linear regression model

Eeg Electrode Localization for Reading-Writing Neuropathway: Spectral Analysis Approach

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