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

Radek Martínek, Martina Ládrová, Michaela Šidiková, René Jaroš, Khosrow Behbehani, Radana Kahánková, Aleksandra Kawala‐Sterniuk

2021Sensors49 citationsDOIOpen Access PDF

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.

Topics & Concepts

Signal processingComputer scienceSIGNAL (programming language)Adaptive filterNoise (video)Digital signal processingBlind signal separationWaveletWavelet transformArtificial intelligenceElectronic engineeringPattern recognition (psychology)EngineeringTelecommunicationsAlgorithmComputer hardwareProgramming languageChannel (broadcasting)Image (mathematics)EEG and Brain-Computer InterfacesECG Monitoring and AnalysisBlind Source Separation Techniques
Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach—Part II: Brain Signals | Litcius