Cognitive Biomedical Engineering
Zahra Soltanifar; Hamid Behnam; Anahita Khorrami Banaraki; Mojtaba Khodadadi; Behnoosh Hamed Ali; Ali Golbazi Mahdipour
Volume 15, Issue 3 , December 2021, , Pages 235-246
Abstract
The pattern of abnormal gaze is observed in individuals with autism spectrum disorders. Studies of eye movements in people with autism have shown significant difference in the pattern of staring at the eyes and mouth compared to control groups. Yet, findings have been contradictory to date, and in spite ...
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The pattern of abnormal gaze is observed in individuals with autism spectrum disorders. Studies of eye movements in people with autism have shown significant difference in the pattern of staring at the eyes and mouth compared to control groups. Yet, findings have been contradictory to date, and in spite of the fact that previous studies on eye dazzling in people with autism are expanding, the findings still do not appear to be consistent. Thus, we tracked eye movements in face processing for 25 teenagers with autism and 25 teenagers from the control group to examine any abnormal concentration in the facial areas. Experimental task used in this study includes standard images of the emotional states of the male and female faces (roundness of the face) in the state of anger, surprise, happiness, sadness and neutrality and subjects looked at these faces, while the eye tracker recorded their eye movements. In this task, they were required to select the displayed emotional state by the reply box. The selected Boosted Trees Ensemble classifier was able to use features related to the total data received from eye tracking in face segmentation into 8 areas (forehead, right and left eye, right and left cheek, nose, mouth and chin) with an accuracy of 83.31% in separating the two groups of autism and control. Moreover, in the study of facial components, left eye, left cheek, right cheek, and right eye, with 84.18%, 83.85%, 82.73% and 81.25% accuracy respectively, were able to make the most difference in the classification. Non-normal patterns in eye gaze can be very important because biomarkers indicate a condition that can be used for early diagnosis. It can also be a guide for researchers to design a game based on the results of this paper to improve the social interactions by strengthening eye contact for people with autism.
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.
Ghasem Sadeghi Bajestani; Abbas Monzavi; Seyed Mohammad Reza Hashemi Golpayegani; Farah Ashrafzadeh
Volume 11, Issue 2 , June 2017, , Pages 167-185
Abstract
Autism spectrum disorder (ASD) is a common disorder among children which despite painstakingly effort, it is not yet possible to be precisely detected using paraclinical methods. On the other hand, early detection, before 18th month, has pivotal role in treatment procedure. In this study, we present ...
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Autism spectrum disorder (ASD) is a common disorder among children which despite painstakingly effort, it is not yet possible to be precisely detected using paraclinical methods. On the other hand, early detection, before 18th month, has pivotal role in treatment procedure. In this study, we present a method for early diagnosis of ASD based on the qualitative analysis of the Electroencephalogram (EEG) signal. We develop a new domain for quantifying the quality of interaction is present. We name it 'stretching – folding space’ (SFS). This domain is based on cybernetics, holistic and information-based analysis approaches. Therefore, it provides a non-deterministic approach to the biosignals. We collected data from 60 normal and 60 children with ASD in the range of 3-10 years old. We extracted features from the data in the SFS domain. The design of the study is self-controlled, meaning that each child serves as his/her own control. Each subject in the study watched a cartoon with and without sound, and the EEG signals were recorded. Statistical tests are applied on the extracted qualitative features in the SFS domain. The difference between the features of the data for each group (normal and ASD) was extracted, and the difference were compared between the groups. The results indicate that there is a statistically significant difference between the SFS features of normal and autism children. We conclude that our proposed method can serve as a new signal processing tool for diagnosing autism.
