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Information on brain state and functionality could be obtained from Electroencephalograph (EEG) signal and is suitable to be used in analyzing brain disorders such as dyslexia. Our work here concerns on optimize setting in the classification of EEG signal for capable dyslexic and normal children using KNN (K-Nearest Neighbour) classifier. Discrete Wavelet Transform (DWT) with Daubechies of order 8...
Several studies have reported that Electroencephalograph (EEG) could provide a practical solution towards giving information with regards to brain functionalities. In the classification of EEG signals of dyslexic children, using a large number of electrodes would result in longer preparation time and noisy signals due to the uncomfortable feeling of wearing a cumbersome headset. This paper describes...
Electroencephalograph (EEG) signal provides information on brain functionalities where electrodes are placed on the surface of the scalp and is suitable in analyzing neurological based disorder such as dyslexia. Known to cause learning disorder, dyslexic tends to utilize different areas of the brain in processing information compared to that of a normal learner. Being non-stationary, the wavelet theory...
Children with dyslexia or known as specific reading disability, have problem in recognizing some words compare to normal children. In this study, electroencephalogram obtained from dyslexic children during writing words, were analyzed. The EEG signals recorded from 4 channels; C3, C4, P3 and P4 were filtered using a band pass filter with frequency range of 14 to 30 Hz. The signals were analyzed using...
Electroencephalogram (EEG) is one of the methods to detect dyslexia in children. Dyslexia has to be detected at an early stage to help the children to excel in their study and later be successful in life. In this study, the EEG signals generated from dyslexic and normal children during relax and writing words were processed, analysed and compared. Four electrodes; C3, C4, P3 and P4 were used in the...
EEG signal contain massive information on brain activities which can be extracted by filtering and processing the signal at specific frequency. The similarity in the EEG signals obtained during actual and imagined writing exists and can be revealed using good representation of the signals. A technique called Autoregressive (AR) is able to model the EEG signals which can be used as input feature for...
Electroencephalogram (EEG) is a tool to record and measure activity of the brain. The spontaneous electrical activity of the brain causes by ionic current flows within the neurons of the brain is collected from electrodes that are placed on the scalp. Analysis on EEG can help us to study the relation between motor imaginary and actual movement during a specific task. EEG data recorded during actual...
Imagined writing is one of the techniques that may improve writing disorder when brain is trained to perform the activity. The imagined writing activity embedded in EEG signal can be extracted and classified using Autoregressive model and Multi Layer Perceptron. This paper describes the classification of imagined writing letters from EEG signals using Multi Layer Perceptron with Autoregression model...
Dyslexia is a neurological disorder which needs to be detected at an early stage to know their specific needs and to help them cope with the problem. One of the ways to detect dyslexia is by using Electroencephalogram (EEG). In this study, the EEG signals recorded from dyslexic's children while performing writing activities were analyzed. The EEG signals were recorded from 4 channels; C3, C4, P3 and...
This paper studies on the characteristics of electroencephalogram (EEG) which generated from writing using right and left hand. The EEG signals were recorded from 4 channels, C3, C4, P3 and P4 and processed using band pass filter (8–30Hz). Two method of analysis were performed; Fast Fourier transform and power spectral density. The results showed that Power Spectral Density can be used to distinguish...
Short-time Fourier Transform (STFT) provides an advantage of revealing the frequency contents of the signal at each time point in the signal. This information can be used to provide control and perform several tasks in Brain Computer Interface system. This paper describes the STFT analysis of EEG signals obtained during relaxing and writing, The results of the STFT analysis showed that there are significant...
Signal processing is an operation design for extracting, enhancing, storing and transmitting useful content of information. In extracting information from the electroencephalogram, digital signal processing techniques are used. In this paper, the EEG signals generated by 2 channels C3 and P3, before and during writing were recorded, which are then filtered using a band pass filter with frequency range...
Electroencephalogram consists of hand movement information that can be extracted using suitable digital signal processing techniques. In this study, the EEG signals generated from hand grasping and writing were recorded from 4 channels; C3, C4, P3 and P4 and filtered using band pass filter with frequency range of 8 Hz to 30 Hz. The signal was then analysed using Fast Fourier Transform. Analysis of...
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