Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Farzaneh Dasar; Majid Ghoshuni; Ghasem Sadeghi Bajestani
Volume 14, Issue 1 , May 2020, , Pages 13-22
Abstract
Autism spectrum disorder is a developmental disorder that involves disorders in social interaction and communication and repetitive or stereotypical behavior. In some children with autism, the sensitivity to acoustic stimuli is much higher than normal (hypersensitive) versus in some other children, this ...
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Autism spectrum disorder is a developmental disorder that involves disorders in social interaction and communication and repetitive or stereotypical behavior. In some children with autism, the sensitivity to acoustic stimuli is much higher than normal (hypersensitive) versus in some other children, this sensitivity is less than normal (hyposensitive). In this study a method for evaluation of auditory system of hypersensitive and hyposensitive autism children using event related potentials (ERPs) was presented. The EEG signal was recorded from 10 autism children (2 girls) with average age of 7.7±2.31 years. In order to record ERPs, 2000 audio stimulation based on the MissMatch Negetivity (MMN) Pattern was presented to participants. These stimulus include 1600 standard sounds with a frequency of 1000 Hz, deviant at 1300 Hz, and noise at frequencies of 1500-1000, 500 and 2000 Hz. In order to analyze ERP data, 18 time domain features have been extracted from the ERP components in all three types of stimulation (standard, deviation, noise). Based on the results, in the deviant stimuli, total positive area of the Pz channel in the hypersensitive group was significantly increased (p=0.028) compared to the hyposensetive group. Also, in the noise stimuli, total positive area in C4 and Pz channels has significantly increased (p=0.028, p=0.009) in the hyposensitive group compared to hypersensetive group. In conclusion, when hypersensitive children were exposed to deviant stimulue, neural activity was increased in parietal lobe, wheras in hyposensitive children neural activity increased in central and parietal lobe during noise stimulue. Therefore, this method can be useful in assessing children's autism spectrum in terms of hearing loss sensitivity.
Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing
Mahdi Zolfagharzadeh Kermani; Mohammad Ali Khalilzadeh; Majid Ghoshuni; Peyman Hashemian
Volume 9, Issue 3 , December 2015, , Pages 243-251
Abstract
Evaluation and measurement of parameters associated with methamphetamine craving can be a valuable tool in the management and intervention programs related to methamphetamine use and dependence. We believe that quantitative electroencephalography (EEG) have brought about a revolution in identification ...
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Evaluation and measurement of parameters associated with methamphetamine craving can be a valuable tool in the management and intervention programs related to methamphetamine use and dependence. We believe that quantitative electroencephalography (EEG) have brought about a revolution in identification the neurologic infrastructure of craving processing. This study has been conducted aimed to design and develop a new method to measure baseline craving in methamphetamine-dependent patients using EEG signals in neurofeedback therapy for separation of the three modes of low, medium, and high craving. For this purpose, 10 methamphetamine abusers were selected by available method in terms of age, sex and IQ. All patients received 10 sessions of neurofeedback therapy with alpha-theta protocol. During the period of treatment with neurofeedback, before and 60 minutes after each training session, at rest state, on Pz, for 2 minutes and 10 seconds EEG was recorded. To labeling EEG signals we have used Desire for Drug Questionnaire (DDQ). After collecting the required data from signals, time, frequency and nonlinear features were extracted. Then by calculating the linear correlation coefficient of the two variables and variance analysis on three levels optimized and effective features were selected. Finally, using fuzzy classifier, those features were separated into three classes of low, medium and high craving. According to the results, separation accuracy of EEG signals in three classes by K-fold Cross-Validation (KCV)method was 96.67% and test data was 75.15%. This study showed in addition to estimating baseline craving in methamphetamine abusers by quantifying EEG we can optimize the number of training sessions for participants.
Majid Ghoshuni; Mohammad Ali Khalilzadeh; Ali Moghimi
Volume 1, Issue 4 , June 2007, , Pages 251-267
Abstract
Episodic memory is the explicit recollection of incidents occurred at a particular time and place in One’s Personal Past. In This Study, Detection of Episodic Memory Activity In Event Related Potentials (ERPs) was done. ERPs were recorded while the subjects made old/new recognition judgments on ...
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Episodic memory is the explicit recollection of incidents occurred at a particular time and place in One’s Personal Past. In This Study, Detection of Episodic Memory Activity In Event Related Potentials (ERPs) was done. ERPs were recorded while the subjects made old/new recognition judgments on the new unstudied meaningless pictures and the old pictures which had been presented at the study phase. In order to extract the features correlated with the episodic memory activity, time and time-frequency features were extracted from ERPs. Wavelet method was implemented for feature extraction in time-frequency. Independent sample test has was for detection of the separable degree the between old/new ERPs. Furthermore, by using stepwise linear discriminate analysis, ERP signals were classified to old and new classes. Ultimately for better classification between old/new ERPs, Multilayer Perceptron was implemented, and for best feature selection, genetic algorithm was used. In the best results, by using time domain features extracted from Pz channel, 100% accuracy in the training and test data was obtained.
