Title :
Identification of working memory impairments in normal children using wavelet approach
Author :
Mohd Tumari, S.Z. ; Sudirman, Rubita ; Ahmad, A.H.
Author_Institution :
Dept. of Electron. Eng., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
The aim of this study was to explore the working memory of children through three assessments of remembering pictures and on mathematical skills. This was done by identifying whether normal right-handed children use their left brain to stimulate the task and investigating the early stages of working memory problem in children. For children, working memory has its limits where the child will lose some information when there is too much information. If that is the case, then the child is known as having impairment in his or her working memory. In this study, the acquisition of working memory data was recorded using Neurofax EEG 9200. The EEG signals were captured using Neuroband electrodes placed at the pre-frontal cortex area of the head. The three assessments were analyzed using Wavelet Transform. Parameter extraction for mean and standard deviation value at the four channels F3, F4, F7 and F8 were averaged and the result showed different increment and decrement for the entire practical assessments. The values of mean at the consequent assessment for Phase I were male=2.25 and female=2.56; Phase II were male=5.23 and female=2.17; and for assessment on mathematical skills, the values were male=2.32 and female=2.54. The result shows that normal children have a good working memory.
Keywords :
biomedical electrodes; data acquisition; electroencephalography; medical signal processing; neurophysiology; paediatrics; wavelet transforms; EEG signals; Neurofax EEG 9200; electroencephalogram; left brain; mathematical skills; neuroband electrodes; normal right-handed children; parameter extraction; prefrontal cortex area; standard deviation; wavelet approach; wavelet transform; working memory data acquisition; working memory impairments; working memory problem; Electroencephalograph; parameter extraction; prefrontal cortex; wavelet transform; working memory;
Conference_Titel :
Industrial Electronics and Applications (ISIEA), 2012 IEEE Symposium on
Conference_Location :
Bandung
Print_ISBN :
978-1-4673-3004-6
DOI :
10.1109/ISIEA.2012.6496653