These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
4. Online Automatic Artifact Rejection using the Real-time EEG Source-mapping Toolbox (REST). Pion-Tonachini L; Hsu SH; Chang CY; Jung TP; Makeig S Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():106-109. PubMed ID: 30440352 [TBL] [Abstract][Full Text] [Related]
5. EEG artifact elimination by extraction of ICA-component features using image processing algorithms. Radüntz T; Scouten J; Hochmuth O; Meffert B J Neurosci Methods; 2015 Mar; 243():84-93. PubMed ID: 25666892 [TBL] [Abstract][Full Text] [Related]
6. Ensemble Deep Neural Network for Automatic Classification of EEG Independent Components. Lopes F; Leal A; Medeiros J; Pinto MF; Dourado A; Dumpelmann M; Teixeira C IEEE Trans Neural Syst Rehabil Eng; 2022; 30():559-568. PubMed ID: 35213313 [TBL] [Abstract][Full Text] [Related]
7. A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings. Tamburro G; Fiedler P; Stone D; Haueisen J; Comani S PeerJ; 2018; 6():e4380. PubMed ID: 29492336 [TBL] [Abstract][Full Text] [Related]
8. A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components. Dharmaprani D; Nguyen HK; Lewis TW; DeLosAngeles D; Willoughby JO; Pope KJ Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():825-828. PubMed ID: 28268452 [TBL] [Abstract][Full Text] [Related]
9. Automatic Independent Component Scalp Map Analysis of Electroencephalogram During Motor Preparation. Cheema MS; Dutta A Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():4689-4692. PubMed ID: 30441396 [TBL] [Abstract][Full Text] [Related]
10. A practical guide to the selection of independent components of the electroencephalogram for artifact correction. Chaumon M; Bishop DV; Busch NA J Neurosci Methods; 2015 Jul; 250():47-63. PubMed ID: 25791012 [TBL] [Abstract][Full Text] [Related]
11. Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings. Croce P; Zappasodi F; Marzetti L; Merla A; Pizzella V; Chiarelli AM IEEE Trans Biomed Eng; 2019 Aug; 66(8):2372-2380. PubMed ID: 30582523 [TBL] [Abstract][Full Text] [Related]
12. Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition. Artoni F; Delorme A; Makeig S Neuroimage; 2018 Jul; 175():176-187. PubMed ID: 29526744 [TBL] [Abstract][Full Text] [Related]
13. A Toolbox and Crowdsourcing Platform for Automatic Labeling of Independent Components in Electroencephalography. Soghoyan G; Ledovsky A; Nekrashevich M; Martynova O; Polikanova I; Portnova G; Rebreikina A; Sysoeva O; Sharaev M Front Neuroinform; 2021; 15():720229. PubMed ID: 34924988 [TBL] [Abstract][Full Text] [Related]
14. An Unsupervised Method for Artefact Removal in EEG Signals. Mur A; Dormido R; Duro N Sensors (Basel); 2019 May; 19(10):. PubMed ID: 31109062 [TBL] [Abstract][Full Text] [Related]
15. Hybrid algorithm for multi artifact removal from single channel EEG. Noorbasha SK; Florence Sudha G Biomed Phys Eng Express; 2021 May; 7(4):. PubMed ID: 33930879 [TBL] [Abstract][Full Text] [Related]