Sensors, Vol. 22, Pages 103: Pilot Study on Analysis of Electroencephalography Signals from Children with FASD with the Implementation of Naive Bayesian Classifiers

Sensors, Vol. 22, Pages 103: Pilot Study on Analysis of Electroencephalography Signals from Children with FASD with the Implementation of Naive Bayesian Classifiers Sensors doi: 10.3390/s22010103 Authors: Katarzyna Anna Dyląg Wiktoria Wieczorek Waldemar Bauer Piotr Walecki Bozena Bando Radek Martinek Aleksandra Kawala-Sterniuk In this paper Naive Bayesian classifiers were applied for the purpose of differentiation between the EEG signals recorded from children with Fetal Alcohol Syndrome Disorders (FASD) and healthy ones. This work also provides a brief introduction to the FASD itself, explaining the social, economic and genetic reasons for the FASD occurrence. The obtained results were good and promising and indicate that EEG recordings can be a helpful tool for potential diagnostics of FASDs children affected with it, in particular those with invisible physical signs of these spectrum disorders.
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research