Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part II: Brain Signals

Abstract

As it was mentioned in the previous part of this work (Part I)—the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work—various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

Pilot Study on Analysis of Electroencephalography Signals from Children with FASD with the Implementation of Naive Bayesian Classifiers

“…These initial results indicate that on the basis of the EEG it is possible to detect FASD, even in children and adolescents without visible external features, making it is a promising and efficient tool, whichcan potentially support the diagnostic process. It is non-invasive and inexpensive compared to other medical imagining methods [ 33 , 34 ]. The main problem with the FASD diagnosis is the various applied criteria, which differ across countries and even among clinics themselves.…”

“…This is the current trend and future in biomedical engineering. Among these methods are blind separation algorithms, such as independent component analysis (ICA) combined with adaptive filtering [ 34 ]. The authors are also planning to combine the naive Bayesian classifier with ICA and to customize and improve threshold-based methods, as described in [ 59 ].…”

“…In order to remove the electrical interference of 50 Hz a notch filter was applied. The electrodes were placed in accordance with the double-banana system, instead of the classic “10–20” arrangement, which is a typical clinical montage used usually in epilepsy-related studies [ 34 , 35 , 36 ].…”

“…In order to remove the electrical interference of 50 Hz a notch filter was applied. The electrodes were placed in accordance with the double-banana system, instead of the classic "10-20" arrangement, which is a typical clinical montage used usually in epilepsy-related studies [34][35][36] Signals recorded with the electrodes (18 channels) placed in the following locations: 'Fp2-F8', 'F8-T4', 'T4-T6', 'T6-O2', 'Fp1-F7', 'F7-T3', 'T3-T5', 'T5-O1', 'Fp2-F4', 'F4-C4', 'C4-P4', 'P4-O2', 'Fp1-F3', 'F3-C3', 'C3-P3', 'P3-O1', 'Fz-Cz', 'Cz-Pz'.…”

“…A thorough literature study did not provide any information regarding using naive Bayesian classifiers for the FASD assessment in children and/or adolescents based on EEG data analysis. In our opinion, using EEG is safe, inexpensive and may provide useful information, which cannot be detected using other screening tool, such as those based on eye-movement or psychometrics [ 33 , 34 ].…”