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: Katarzyna Anna Dyl ąg Wiktoria Wieczorek Waldemar Bauer Piotr Walecki Bozena Bando Radek Martinek Aleksandra Kawala-Sterniuk Tags: Article Source Type: research
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