The aim of this study is to recognize the best and suitable wavelet family for analyzing cognitive memory using Electroencephalograph (EEG) signal. The participant was given some visual stimuli during the study phase, which were a sequence of pictures that had to be remembered to acquire the EEG signal. The Neurofax EEG 9200 was used to record the acquisition of cognitive memory at channel Fz. The raw EEG signals were analyzed using Wavelet Transform. A lot of mother wavelets can be used for analyzing the signal, but do not lose any information on the wavelet, some predictions must be made beforehand. The criteria of the EEG signal were narrowed down to the Daubechies, Symlets and Coiflets, and it is the final selection depending on their Mean Square Error (MSE). The best solution would have the least difference between the original and constructed signal. Results indicated that the Daubechies wavelet at a level of decomposition of 4 (db4) was the most suitable wavelet for pre-processing the raw EEG signal of cognitive memory. To conclude, choosing the suitable wavelet family is more important than relying on the MSE value alone to successfully perform a wavelet transformation
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 prefrontal 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.
This study was designed to classify and determine the Event-Related Potentials (ERPs) signal pattern of normal children on visual response. Thirty-eight children aged between 10 to 12 years old were subjected to a two-phase computer-based assessment while their working memory activity was recorded using a Neurofax-EEG 9200 machine. For children, it is anticipated that some information can be lost when there is too much information given at any one time due to limited memory capacity and this is a type of memory impairment. Based on the visual stimulus responses, EEG signal were recorded and captured from channel location at Fz. This paper explains the extraction of raw EEG signals into grand mean ERPs signal which to determine the pattern of signal developed. The ERPs concerning latency and amplitude variability of the P300 component was evaluated. The analysis was based on Discrete Wavelet Transform (DWT) algorithm and focused on alpha rhythm. Results indicated that the Daubechies wavelet at a decomposition level of 4 (db4) was the most suitable wavelet for pre-processing raw EEG signal of working memory. A significant increase of latency was detected in children aged 10 to 12 years old at channel Fz (frontal midline) when the visual stimuli became more difficult. For amplitude variability, the girls gave higher amplitude at Phase 1. These results supported the concept of increased cognitive memory in children.
This study is to investigate the Event-Related Potentials (ERP) from the background of Electroencephalograph (EEG) signal for working memory retention by using visual stimuli. The proposed analysis of ERP signal is to predict the performance of working memory retention for various frequency bands such as gamma, beta, alpha, theta and delta. This study is intended to process the EEG data into ERP data and analyze the ERP signal based on power spectrum density. This method is applied to data of normal children with age between 7 to 12 years old. Result showed that alpha power band increases during working memory retention towards visual stimuli compared to the other frequency band. 9 years old has the highest amplitude alpha power compared to the other group of age. Therefore, the alpha power band at the prefrontal cortex will be used for the next analysis of the working memory retention.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.