A practical EEG study on autism using Artificial Neural Networks

Authors:
Xiaozhen You;Nina Teng;Melvin Ayala;Lu Wang;Armando Barreto;Naphtali Rishe;Malek Adjouadi
Affiliations:
Florida International University, Miami, FL;Florida International University, Miami, FL;Florida International University, Miami, FL;Florida International University, Miami, FL;Florida International University, Miami, FL;Florida International University, Miami, FL;Florida International University, Miami, FL
Venue:
GVE '07 Proceedings of the IASTED International Conference on Graphics and Visualization in Engineering
Year:
2007

Citing 1
Cited 1

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Abstract

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.