Automated preprocessing of 64 channel electroenchephalograms recorded by biosemi instruments
Preprocessing is a mandatory step in electroencephalogram (EEG) signal analysis. Overcoming challenges posed by high noise levels and substantial amplitude artifacts, such as blink-induced electrooculogram (EOG) and muscle-related electromyogram (EMG) interference, is imperative. The signal-to-noise...
Elmentve itt :
| Szerzők: | |
|---|---|
| Dokumentumtípus: | Cikk |
| Megjelent: |
2023
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| Sorozat: | METHODSX
11 |
| Tárgyszavak: | |
| doi: | 10.1016/j.mex.2023.102378 |
| mtmt: | 34177906 |
| Online Access: | http://publicatio.bibl.u-szeged.hu/28658 |
| LEADER | 01963nab a2200301 i 4500 | ||
|---|---|---|---|
| 001 | publ28658 | ||
| 005 | 20231109115850.0 | ||
| 008 | 231109s2023 hu o 0|| Angol d | ||
| 022 | |a 2215-0161 | ||
| 024 | 7 | |a 10.1016/j.mex.2023.102378 |2 doi | |
| 024 | 7 | |a 34177906 |2 mtmt | |
| 040 | |a SZTE Publicatio Repozitórium |b hun | ||
| 041 | |a Angol | ||
| 100 | 1 | |a Kiss Ádám | |
| 245 | 1 | 0 | |a Automated preprocessing of 64 channel electroenchephalograms recorded by biosemi instruments |h [elektronikus dokumentum] / |c Kiss Ádám |
| 260 | |c 2023 | ||
| 300 | |a 7 | ||
| 490 | 0 | |a METHODSX |v 11 | |
| 520 | 3 | |a Preprocessing is a mandatory step in electroencephalogram (EEG) signal analysis. Overcoming challenges posed by high noise levels and substantial amplitude artifacts, such as blink-induced electrooculogram (EOG) and muscle-related electromyogram (EMG) interference, is imperative. The signal-to-noise ratio significantly influences the reliability and statistical significance of subsequent analyses. Existing referencing approaches employed in multi-card systems, like using a single electrode or averaging across multiple electrodes, fall short in this respect. In this article, we introduce an innovative referencing method tailored to multi-card instruments, enhancing signal fidelity and analysis outcomes. Our proposed signal processing loop not only mitigates blink-related artifacts but also accurately identifies muscle activity. This work contributes to advancing EEG analysis by providing a robust solution for artifact removal and enhancing data integrity. | |
| 650 | 4 | |a Számítás- és információtudomány | |
| 650 | 4 | |a Általános orvostudomány | |
| 700 | 0 | 1 | |a Huszár Olívia Mária |e aut |
| 700 | 0 | 1 | |a Bodosi Balázs |e aut |
| 700 | 0 | 1 | |a Eördegh Gabriella |e aut |
| 700 | 0 | 1 | |a Tót Kálmán |e aut |
| 700 | 0 | 1 | |a Nagy Attila |e aut |
| 700 | 0 | 1 | |a Kelemen András |e aut |
| 856 | 4 | 0 | |u http://publicatio.bibl.u-szeged.hu/28658/1/Kissetal2023.pdf |z Dokumentum-elérés |