Paper Info
Title
Resting State Eeg-Based Diagnosis Of Autism Via Elliptic Area Of Continuous Wavelet Transform Complex Plot
Abstract
Autism is a developmental disorder that influences social communication skills. It is currently diagnosed only by behavioral assessment. The assessment is susceptible to the experience of the examiner as well as to the descriptive scaling standard. This paper presents a computer aided approach to discrimination between neuro-typical and autistic children. A new method- based on the computing of the elliptic area of the Continuous Wavelet Transform complex plot of resting state EEG- is presented. First, the complex values of CWT, as a function of both time and frequency, are calculated for every EEG channel. Second, the CWT complex plot is obtained by plotting the real parts of the resulted CWT values versus the related imaginary components. Third, the 95% confidence value of the elliptic area of the complex plot is computed for every channel for both autistic and healthy subjects; and the obtained values are considered as the first set of features. Fourth, three additional features are computed for every channel: the average CWT, the maximum EEG amplitude, and the maximum real part of CWT. The classification of those features is realized through artificial neural network (ANN). The obtained accuracy, sensitivity and specificity values are: 95.9%, 96.7%, and 95.1% respectively.
Year
DOI
Venue
2020
10.3233/JIFS-189176
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
DocType
Volume
Autism, EEG, CWT, Elliptic area, classification
Journal
39
Issue
ISSN
Citations 
6
1064-1246
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Enas Abdulhay125616.49
Maha Alafeef261.35
Hikmat Hadoush300.34
N. Arunkumar400.68