Thesis Open Access
Autistic Spectrum Disorder (ASD) is characterized by a delay in expressing and
interpreting other emotions as well as having difficulties with social abilities. It
covers a very broad range of diagnosis and it affects 1% of the world population,
the differences between the various types are not well defined and the reason behind
this disease is not well understood. Therefore, studies such as this are being
carried out towards better comprehending and explaining the unknown of this disease.
In this work, a group of ASD children and a group of typical children were
observed by recording their EEG signal and verbal answers while they were exposed
to audio-visual stimuli with an emotional character and were asked to identify such
emotion. First, correlation between EEG features and verbal and expected response
was computed to confirm EEG may be used to interpret emotions. This was confirmed.
Next, EEG features were correlated with audio features to observe which
audio category (harmony, melody, rhythm, or timbre) is most relevant when interpreting
an emotion. Results from this study suggest timbre being most relevant.
This study is intended to obtain further information about the relationship between
music and ASD patients that could be employed to improve music therapy.