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

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6343
Author(s):  
Radek Martinek ◽  
Martina Ladrova ◽  
Michaela Sidikova ◽  
Rene Jaros ◽  
Khosrow Behbehani ◽  
...  

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.

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5186
Author(s):  
Radek Martinek ◽  
Martina Ladrova ◽  
Michaela Sidikova ◽  
Rene Jaros ◽  
Khosrow Behbehani ◽  
...  

Advanced signal processing methods are one of the fastest developing scientific and technical areas of biomedical engineering with increasing usage in current clinical practice. This paper presents an extensive literature review of the methods for the digital signal processing of cardiac bioelectrical signals that are commonly applied in today’s clinical practice. This work covers the definition of bioelectrical signals. It also covers to the extreme extent of classical and advanced approaches to the alleviation of noise contamination such as digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation and wavelet transform.


Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6064
Author(s):  
Radek Martinek ◽  
Martina Ladrova ◽  
Michaela Sidikova ◽  
Rene Jaros ◽  
Khosrow Behbehani ◽  
...  

Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).


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