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您的检索式：作者名="Christopher Harshaw"
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| 1 | Integration of Facial Thermography in EEG-based Classification of ASD显示文摘Autism spectrum disorder(ASD)is a neurodevelopmental disorder affecting social,communicative,and repetitive behavior.The phenotypic heterogeneity of ASD makes timely and accurate diagnosis challenging,requiring highly trained clinical practitioners.The development of automated approaches to ASD classification,based on integrated psychophysiological measures,may one day help expedite the diagnostic process.This paper provides a novel contribution for classifing ASD using both thermographic and EEG data.The methodology used in this study extracts a variety of feature sets and evaluates the possibility of using several learning models.Mean,standard deviation,and entropy values of the EEG signals and mean temperature values of regions of interest(ROIs)in facial thermographic images were extracted as features.Feature selection is performed to filter less informative features based on correlation.The classification process utilizes Naive Bayes,random forest,logistic regression,and multi-layer perceptron algorithms.The integration of EEG and thermographic features have achieved an accuracy of 94%with both logistic regression and multi-layer perceptron classifiers.The results have shown that the classification accuracies of most of the learning models have increased after integrating facial thermographic data with EEG. | Dilantha Haputhanthri Gunavaran Brihadiswaran Sahan Gunathilaka Dulani Meedeniya Sampath Jayarathna Mark Jaime Christopher Harshaw | 2020 | International Journal of Automation and computing2020，17，6： | 1 |
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