587 related articles for article (PubMed ID: 30452976)
1. An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation.
Chowdhury A; Raza H; Meena YK; Dutta A; Prasad G
J Neurosci Methods; 2019 Jan; 312():1-11. PubMed ID: 30452976
[TBL] [Abstract][Full Text] [Related]
2. Exploring high-density corticomuscular networks after stroke to enable a hybrid Brain-Computer Interface for hand motor rehabilitation.
Pichiorri F; Toppi J; de Seta V; Colamarino E; Masciullo M; Tamburella F; Lorusso M; Cincotti F; Mattia D
J Neuroeng Rehabil; 2023 Jan; 20(1):5. PubMed ID: 36639665
[TBL] [Abstract][Full Text] [Related]
3. Enhancement of EEG-EMG coupling detection using corticomuscular coherence with spatial-temporal optimization.
Sun J; Jia T; Li Z; Li C; Ji L
J Neural Eng; 2023 May; 20(3):. PubMed ID: 37068482
[No Abstract] [Full Text] [Related]
4. Corticomuscular and Intermuscular Coupling in Simple Hand Movements to Enable a Hybrid Brain-Computer Interface.
Colamarino E; de Seta V; Masciullo M; Cincotti F; Mattia D; Pichiorri F; Toppi J
Int J Neural Syst; 2021 Nov; 31(11):2150052. PubMed ID: 34590990
[TBL] [Abstract][Full Text] [Related]
5. Brain oscillatory signatures of motor tasks.
Ramos-Murguialday A; Birbaumer N
J Neurophysiol; 2015 Jun; 113(10):3663-82. PubMed ID: 25810484
[TBL] [Abstract][Full Text] [Related]
6. BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients.
Casey A; Azhar H; Grzes M; Sakel M
Disabil Rehabil Assist Technol; 2021 Jul; 16(5):525-537. PubMed ID: 31711336
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Is EMG a Viable Alternative to BCI for Detecting Movement Intention in Severe Stroke?
Balasubramanian S; Garcia-Cossio E; Birbaumer N; Burdet E; Ramos-Murguialday A
IEEE Trans Biomed Eng; 2018 Dec; 65(12):2790-2797. PubMed ID: 29993449
[TBL] [Abstract][Full Text] [Related]
9. Single-Trial EEG-EMG coherence analysis reveals muscle fatigue-related progressive alterations in corticomuscular coupling.
Siemionow V; Sahgal V; Yue GH
IEEE Trans Neural Syst Rehabil Eng; 2010 Apr; 18(2):97-106. PubMed ID: 20371421
[TBL] [Abstract][Full Text] [Related]
10. A comprehensive review of EEG-based brain-computer interface paradigms.
Abiri R; Borhani S; Sellers EW; Jiang Y; Zhao X
J Neural Eng; 2019 Feb; 16(1):011001. PubMed ID: 30523919
[TBL] [Abstract][Full Text] [Related]
11. An online hybrid BCI system based on SSVEP and EMG.
Lin K; Cinetto A; Wang Y; Chen X; Gao S; Gao X
J Neural Eng; 2016 Apr; 13(2):026020. PubMed ID: 26902294
[TBL] [Abstract][Full Text] [Related]
12. Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations.
Park SA; Hwang HJ; Lim JH; Choi JH; Jung HK; Im CH
Med Biol Eng Comput; 2013 May; 51(5):571-9. PubMed ID: 23325145
[TBL] [Abstract][Full Text] [Related]
13. Brain-computer interface (BCI) operation: signal and noise during early training sessions.
McFarland DJ; Sarnacki WA; Vaughan TM; Wolpaw JR
Clin Neurophysiol; 2005 Jan; 116(1):56-62. PubMed ID: 15589184
[TBL] [Abstract][Full Text] [Related]
14. Design a Novel BCI for Neurorehabilitation Using Concurrent LFP and EEG Features: A Case Study.
Feng Z; Sun Y; Qian L; Qi Y; Wang Y; Guan C; Sun Y
IEEE Trans Biomed Eng; 2022 May; 69(5):1554-1563. PubMed ID: 34582344
[TBL] [Abstract][Full Text] [Related]
15. An embedded implementation based on adaptive filter bank for brain-computer interface systems.
Belwafi K; Romain O; Gannouni S; Ghaffari F; Djemal R; Ouni B
J Neurosci Methods; 2018 Jul; 305():1-16. PubMed ID: 29738806
[TBL] [Abstract][Full Text] [Related]
16. EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine.
Gao L; Cheng W; Zhang J; Wang J
Rev Sci Instrum; 2016 Aug; 87(8):085110. PubMed ID: 27587163
[TBL] [Abstract][Full Text] [Related]
17. Cortical effects of user training in a motor imagery based brain-computer interface measured by fNIRS and EEG.
Kaiser V; Bauernfeind G; Kreilinger A; Kaufmann T; Kübler A; Neuper C; Müller-Putz GR
Neuroimage; 2014 Jan; 85 Pt 1():432-44. PubMed ID: 23651839
[TBL] [Abstract][Full Text] [Related]
18. A Novel Technique for Selecting EMG-Contaminated EEG Channels in Self-Paced Brain-Computer Interface Task Onset.
Song Y; Sepulveda F
IEEE Trans Neural Syst Rehabil Eng; 2018 Jul; 26(7):1353-1362. PubMed ID: 29985144
[TBL] [Abstract][Full Text] [Related]
19. Enhanced Descending Corticomuscular Coupling During Hand Grip With Static Force Compared With Enhancing Force.
Gao L; Wu H; Cheng W; Lan B; Ren H; Zhang L; Wang L
Clin EEG Neurosci; 2021 Nov; 52(6):436-443. PubMed ID: 32611201
[TBL] [Abstract][Full Text] [Related]
20. A multiblock PLS model of cortico-cortical and corticomuscular interactions in Parkinson's disease.
Chiang J; Wang ZJ; McKeown MJ
Neuroimage; 2012 Nov; 63(3):1498-509. PubMed ID: 22982102
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]