135 related articles for article (PubMed ID: 37422278)
1. Decoding semantic relatedness and prediction from EEG: A classification method comparison.
Trammel T; Khodayari N; Luck SJ; Traxler MJ; Swaab TY
Neuroimage; 2023 Aug; 277():120268. PubMed ID: 37422278
[TBL] [Abstract][Full Text] [Related]
2. Riemannian classifier enhances the accuracy of machine-learning-based diagnosis of PTSD using resting EEG.
Kim YW; Kim S; Shim M; Jin MJ; Jeon H; Lee SH; Im CH
Prog Neuropsychopharmacol Biol Psychiatry; 2020 Aug; 102():109960. PubMed ID: 32376342
[TBL] [Abstract][Full Text] [Related]
3. Comparison of subject-independent and subject-specific EEG-based BCI using LDA and SVM classifiers.
Dos Santos EM; San-Martin R; Fraga FJ
Med Biol Eng Comput; 2023 Mar; 61(3):835-845. PubMed ID: 36626112
[TBL] [Abstract][Full Text] [Related]
4. Classification of EEG Using Adaptive SVM Classifier with CSP and Online Recursive Independent Component Analysis.
Antony MJ; Sankaralingam BP; Mahendran RK; Gardezi AA; Shafiq M; Choi JG; Hamam H
Sensors (Basel); 2022 Oct; 22(19):. PubMed ID: 36236694
[TBL] [Abstract][Full Text] [Related]
5. Designing a robust feature extraction method based on optimum allocation and principal component analysis for epileptic EEG signal classification.
Siuly S; Li Y
Comput Methods Programs Biomed; 2015 Apr; 119(1):29-42. PubMed ID: 25704869
[TBL] [Abstract][Full Text] [Related]
6. A comprehensive exploration of machine learning techniques for EEG-based anxiety detection.
Aldayel M; Al-Nafjan A
PeerJ Comput Sci; 2024; 10():e1829. PubMed ID: 38435618
[TBL] [Abstract][Full Text] [Related]
7. Exceeding chance level by chance: The caveat of theoretical chance levels in brain signal classification and statistical assessment of decoding accuracy.
Combrisson E; Jerbi K
J Neurosci Methods; 2015 Jul; 250():126-36. PubMed ID: 25596422
[TBL] [Abstract][Full Text] [Related]
8. Single-Trial Detection of Semantic Anomalies From EEG During Listening to Spoken Sentences.
Tanaka H; Watanabe H; Maki H; Sakti S; Nakamura S
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():977-980. PubMed ID: 30440554
[TBL] [Abstract][Full Text] [Related]
9. A new (semantic) reflexive brain-computer interface: in search for a suitable classifier.
Furdea A; Ruf CA; Halder S; De Massari D; Bogdan M; Rosenstiel W; Matuz T; Birbaumer N
J Neurosci Methods; 2012 Jan; 203(1):233-40. PubMed ID: 21963400
[TBL] [Abstract][Full Text] [Related]
10. Decoding Single-Hand and Both-Hand Movement Directions From Noninvasive Neural Signals.
Wang J; Bi L; Fei W; Guan C
IEEE Trans Biomed Eng; 2021 Jun; 68(6):1932-1940. PubMed ID: 33108279
[TBL] [Abstract][Full Text] [Related]
11. Motor Imagery Classification Based on EEG Sensing with Visual and Vibrotactile Guidance.
Batistić L; Sušanj D; Pinčić D; Ljubic S
Sensors (Basel); 2023 May; 23(11):. PubMed ID: 37299791
[TBL] [Abstract][Full Text] [Related]
12. Single-Trial Decoding of Scalp EEG under Natural Conditions.
Tuckute G; Hansen ST; Pedersen N; Steenstrup D; Hansen LK
Comput Intell Neurosci; 2019; 2019():9210785. PubMed ID: 31143206
[TBL] [Abstract][Full Text] [Related]
13. Multi-feature classifiers for burst detection in single EEG channels from preterm infants.
Navarro X; Porée F; Kuchenbuch M; Chavez M; Beuchée A; Carrault G
J Neural Eng; 2017 Aug; 14(4):046015. PubMed ID: 28474599
[TBL] [Abstract][Full Text] [Related]
14. Person identification from EEG using various machine learning techniques with inter-hemispheric amplitude ratio.
Jayarathne I; Cohen M; Amarakeerthi S
PLoS One; 2020; 15(9):e0238872. PubMed ID: 32915850
[TBL] [Abstract][Full Text] [Related]
15. Machine learning-based classification using electroencephalographic multi-paradigms between drug-naïve patients with depression and healthy controls.
Jang KI; Kim S; Chae JH; Lee C
J Affect Disord; 2023 Oct; 338():270-277. PubMed ID: 37271294
[TBL] [Abstract][Full Text] [Related]
16. A comparison of machine learning methods for classification using simulation with multiple real data examples from mental health studies.
Khondoker M; Dobson R; Skirrow C; Simmons A; Stahl D
Stat Methods Med Res; 2016 Oct; 25(5):1804-1823. PubMed ID: 24047600
[TBL] [Abstract][Full Text] [Related]
17. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.
Lajnef T; Chaibi S; Ruby P; Aguera PE; Eichenlaub JB; Samet M; Kachouri A; Jerbi K
J Neurosci Methods; 2015 Jul; 250():94-105. PubMed ID: 25629798
[TBL] [Abstract][Full Text] [Related]
18. Binary classification of multichannel-EEG records based on the ϵ-complexity of continuous vector functions.
Piryatinska A; Darkhovsky B; Kaplan A
Comput Methods Programs Biomed; 2017 Dec; 152():131-139. PubMed ID: 29054253
[TBL] [Abstract][Full Text] [Related]
19. A large N400 but no BOLD effect--comparing source activations of semantic priming in simultaneous EEG-fMRI.
Geukes S; Huster RJ; Wollbrink A; Junghöfer M; Zwitserlood P; Dobel C
PLoS One; 2013; 8(12):e84029. PubMed ID: 24391871
[TBL] [Abstract][Full Text] [Related]
20. Emotion recognition from single-trial EEG based on kernel Fisher's emotion pattern and imbalanced quasiconformal kernel support vector machine.
Liu YH; Wu CT; Cheng WT; Hsiao YT; Chen PM; Teng JT
Sensors (Basel); 2014 Jul; 14(8):13361-88. PubMed ID: 25061837
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]