193 related articles for article (PubMed ID: 38064955)
1. Fractal Dimension as a discriminative feature for high accuracy classification in motor imagery EEG-based brain-computer interface.
Moaveninejad S; D'Onofrio V; Tecchio F; Ferracuti F; Iarlori S; Monteriù A; Porcaro C
Comput Methods Programs Biomed; 2024 Feb; 244():107944. PubMed ID: 38064955
[TBL] [Abstract][Full Text] [Related]
2. Motor imagery EEG classification based on ensemble support vector learning.
Luo J; Gao X; Zhu X; Wang B; Lu N; Wang J
Comput Methods Programs Biomed; 2020 Sep; 193():105464. PubMed ID: 32283387
[TBL] [Abstract][Full Text] [Related]
3. A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study.
Wang K; Wang Z; Guo Y; He F; Qi H; Xu M; Ming D
J Neuroeng Rehabil; 2017 Sep; 14(1):93. PubMed ID: 28893295
[TBL] [Abstract][Full Text] [Related]
4. Motor Imagery EEG Classification for Patients with Amyotrophic Lateral Sclerosis Using Fractal Dimension and Fisher's Criterion-Based Channel Selection.
Liu YH; Huang S; Huang YD
Sensors (Basel); 2017 Jul; 17(7):. PubMed ID: 28671629
[TBL] [Abstract][Full Text] [Related]
5. Classification of motor imagery EEG using deep learning increases performance in inefficient BCI users.
Tibrewal N; Leeuwis N; Alimardani M
PLoS One; 2022; 17(7):e0268880. PubMed ID: 35867703
[TBL] [Abstract][Full Text] [Related]
6. EEG-based classification of imaginary left and right foot movements using beta rebound.
Hashimoto Y; Ushiba J
Clin Neurophysiol; 2013 Nov; 124(11):2153-60. PubMed ID: 23757379
[TBL] [Abstract][Full Text] [Related]
7. EEG characteristic investigation of the sixth-finger motor imagery and optimal channel selection for classification.
Liu Y; Wang Z; Huang S; Wang W; Ming D
J Neural Eng; 2022 Jan; 19(1):. PubMed ID: 35008079
[No Abstract] [Full Text] [Related]
8. Unraveling motor imagery brain patterns using explainable artificial intelligence based on Shapley values.
Pérez-Velasco S; Marcos-Martínez D; Santamaría-Vázquez E; Martínez-Cagigal V; Moreno-Calderón S; Hornero R
Comput Methods Programs Biomed; 2024 Apr; 246():108048. PubMed ID: 38308997
[TBL] [Abstract][Full Text] [Related]
9. Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.
Tayeb Z; Fedjaev J; Ghaboosi N; Richter C; Everding L; Qu X; Wu Y; Cheng G; Conradt J
Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626132
[TBL] [Abstract][Full Text] [Related]
10. A flexible analytic wavelet transform based approach for motor-imagery tasks classification in BCI applications.
Chaudhary S; Taran S; Bajaj V; Siuly S
Comput Methods Programs Biomed; 2020 Apr; 187():105325. PubMed ID: 31964514
[TBL] [Abstract][Full Text] [Related]
11. Comparison of EEG measurement of upper limb movement in motor imagery training system.
Suwannarat A; Pan-Ngum S; Israsena P
Biomed Eng Online; 2018 Aug; 17(1):103. PubMed ID: 30071853
[TBL] [Abstract][Full Text] [Related]
12. Multi-class EEG classification of motor imagery signal by finding optimal time segments and features using SNR-based mutual information.
Mahmoudi M; Shamsi M
Australas Phys Eng Sci Med; 2018 Dec; 41(4):957-972. PubMed ID: 30338495
[TBL] [Abstract][Full Text] [Related]
13. EEG oscillatory patterns and classification of sequential compound limb motor imagery.
Yi W; Qiu S; Wang K; Qi H; He F; Zhou P; Zhang L; Ming D
J Neuroeng Rehabil; 2016 Jan; 13():11. PubMed ID: 26822435
[TBL] [Abstract][Full Text] [Related]
14. Recognition of EEG Signal Motor Imagery Intention Based on Deep Multi-View Feature Learning.
Xu J; Zheng H; Wang J; Li D; Fang X
Sensors (Basel); 2020 Jun; 20(12):. PubMed ID: 32575798
[TBL] [Abstract][Full Text] [Related]
15. Feature extraction of four-class motor imagery EEG signals based on functional brain network.
Ai Q; Chen A; Chen K; Liu Q; Zhou T; Xin S; Ji Z
J Neural Eng; 2019 Apr; 16(2):026032. PubMed ID: 30699389
[TBL] [Abstract][Full Text] [Related]
16. An EEG channel selection method for motor imagery based brain-computer interface and neurofeedback using Granger causality.
Varsehi H; Firoozabadi SMP
Neural Netw; 2021 Jan; 133():193-206. PubMed ID: 33220643
[TBL] [Abstract][Full Text] [Related]
17. A hybrid BCI based on EEG and fNIRS signals improves the performance of decoding motor imagery of both force and speed of hand clenching.
Yin X; Xu B; Jiang C; Fu Y; Wang Z; Li H; Shi G
J Neural Eng; 2015 Jun; 12(3):036004. PubMed ID: 25834118
[TBL] [Abstract][Full Text] [Related]
18. A penalized time-frequency band feature selection and classification procedure for improved motor intention decoding in multichannel EEG.
Peterson V; Wyser D; Lambercy O; Spies R; Gassert R
J Neural Eng; 2019 Feb; 16(1):016019. PubMed ID: 30623892
[TBL] [Abstract][Full Text] [Related]
19. Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals.
Malan NS; Sharma S
Comput Biol Med; 2019 Apr; 107():118-126. PubMed ID: 30802693
[TBL] [Abstract][Full Text] [Related]
20. A shallow mirror transformer for subject-independent motor imagery BCI.
Luo J; Wang Y; Xia S; Lu N; Ren X; Shi Z; Hei X
Comput Biol Med; 2023 Sep; 164():107254. PubMed ID: 37499295
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
