A PRACTICAL EEG STUDY ON AUTISM USING ARTIFICIAL NEURAL NETWORKS

机译：人工神经网络的自闭症实用脑电图研究

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Autism is characterized as a spectrum of neurodevelopment impairments in communicative, social behavioural, and sensory motor skills. Public concerns about autism have grown in recent years due to the prevalence of its diagnosis in 1 out of 150 young children. Though many researches have been carried out to analyse autistic patients' EEG behaviour, an effective physiological diagnosis for autism does not exist and researchers haven't found a distinguishing pattern to classify autistic and non-autistic subjects. This preliminary study analyses the EEG data to compare patterns of speech and non- speech sound discrimination between 8 non-autistic and 4 autistic teenagers. An Artificial Neural Networks (ANNs) based classifier has been implemented to determine whether EEG data reflects differences from the two types of responses.

机译：自闭症的特征是在交流，社交行为和感觉运动技能方面存在一系列神经发育障碍。近年来，由于自闭症的诊断在150名幼儿中有1名的患病率越来越高，公众对此的关注日益增加。尽管已经进行了许多研究来分析自闭症患者的脑电图行为，但还没有有效的自闭症生理诊断方法，研究人员还没有找到区分自闭症和非自闭症受试者的区分模式。这项初步研究分析了EEG数据，以比较8名非自闭症青少年和4名自闭症青少年的语音和非语音声音辨别模式。已经实现了基于人工神经网络（ANN）的分类器，以确定EEG数据是否反映了两种响应类型的差异。

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来源
《IASTED(International Association of Science and Technology for Development) International Conference on Graphics and Visualization in Engineering; 20070103-05; Clearwater,FL(US)》|2007年|P.41-46|共6页
会议地点 ClearwaterFL(US)
作者
Xiaozhen You; Nina Teng; Melvin Ayala; Lu Wang; Armando Barreto; Naphtali Rishe; Malek Adjouadi;
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Department of Biomedical Engineering Florida International University 10555 W. Flagler Street, Miami FL 33174, U.S.A.;

Department of Electrical and Computer Engineering, Florida International University 10555 W. Flagler Street, Miami FL 33174, U.S.A.;

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原文格式 PDF
正文语种 eng
中图分类工程制图;
关键词
autism; MMN; artificial intelligence; classification; neural networks;

机译：自闭症; MMN;人工智能;分类;神经网络;

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2. Exploratory study of the effect of binaural beat stimulation on the EEG activity pattern in resting state using artificial neural networks [J] . da Silva Junior Mauricio, de Freitas Rafaela Covello, dos Santos Wellington Pinheiro, Cognitive Systems Research . 2019,第MAY期

机译：利用人工神经网络探索双耳节律刺激对静止状态下脑电活动模式的影响
3. Scoring upper-extremity motor function from EEG with artificial neural networks: a preliminary study [J] . Zhang Xin, DArcy Ryan, Menon Carlo Journal of neural engineering . 2019,第3期

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4. A PRACTICAL EEG STUDY ON AUTISM USING ARTIFICIAL NEURAL NETWORKS [C] . Xiaozhen You, Nina Teng, Melvin Ayala, IASTED International Conference on Graphics and Visualization in Engineering . 2007

机译：利用人工神经网络实现自闭症的实践脑电图研究
5. Analysis and Pattern Identification in EEG Signals Using Artificial Neural Networks [D] . Ganesh, Swathi. 2017

机译：使用人工神经网络对脑电信号进行分析和模式识别
6. EEG signal analysis using classification techniques: Logistic regression artificial neural networks support vector machines and convolutional neural networks [O] . Maria Camila Guerrero, Juan Sebastián Parada, Helbert Eduardo Espitia 2021

机译：EEG信号分析使用分类技术：Logistic回归人工神经网络支持向量机和卷积神经网络
7. EEG signal analysis using classification techniques: Logistic regression, artificial neural networks, support vector machines, and convolutional neural networks [O] . Maria Camila Guerrero, Juan Sebastián Parada, Helbert Eduardo Espitia 2021

机译：EEG信号分析使用分类技术：Logistic回归，人工神经网络，支持向量机和卷积神经网络

A PRACTICAL EEG STUDY ON AUTISM USING ARTIFICIAL NEURAL NETWORKS

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