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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 33444236)

  • 1. Hemodynamic responses during standing and sitting activities: a study toward fNIRS-BCI.
    Almulla L; Al-Naib I; Althobaiti M
    Biomed Phys Eng Express; 2020 Jul; 6(5):055005. PubMed ID: 33444236
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Classification of motor imagery and execution signals with population-level feature sets: implications for probe design in fNIRS based BCI.
    Erdoĝan SB; Özsarfati E; Dilek B; Kadak KS; Hanoĝlu L; Akın A
    J Neural Eng; 2019 Apr; 16(2):026029. PubMed ID: 30634177
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study.
    Zimmermann R; Marchal-Crespo L; Edelmann J; Lambercy O; Fluet MC; Riener R; Wolf M; Gassert R
    J Neuroeng Rehabil; 2013 Jan; 10():4. PubMed ID: 23336819
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Application of a common spatial pattern-based algorithm for an fNIRS-based motor imagery brain-computer interface.
    Zhang S; Zheng Y; Wang D; Wang L; Ma J; Zhang J; Xu W; Li D; Zhang D
    Neurosci Lett; 2017 Aug; 655():35-40. PubMed ID: 28663052
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Optimal feature selection from fNIRS signals using genetic algorithms for BCI.
    Noori FM; Naseer N; Qureshi NK; Nazeer H; Khan RA
    Neurosci Lett; 2017 Apr; 647():61-66. PubMed ID: 28336339
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.
    Buccino AP; Keles HO; Omurtag A
    PLoS One; 2016; 11(1):e0146610. PubMed ID: 26730580
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.
    Chiarelli AM; Croce P; Merla A; Zappasodi F
    J Neural Eng; 2018 Jun; 15(3):036028. PubMed ID: 29446352
    [TBL] [Abstract][Full Text] [Related]  

  • 10. fNIRS-GANs: data augmentation using generative adversarial networks for classifying motor tasks from functional near-infrared spectroscopy.
    Nagasawa T; Sato T; Nambu I; Wada Y
    J Neural Eng; 2020 Feb; 17(1):016068. PubMed ID: 31945755
    [TBL] [Abstract][Full Text] [Related]  

  • 11. LASSO Homotopy-Based Sparse Representation Classification for fNIRS-BCI.
    Gulraiz A; Naseer N; Nazeer H; Khan MJ; Khan RA; Shahbaz Khan U
    Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408190
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Classification of prefrontal and motor cortex signals for three-class fNIRS-BCI.
    Hong KS; Naseer N; Kim YH
    Neurosci Lett; 2015 Feb; 587():87-92. PubMed ID: 25529197
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Lower Limb Movement Preparation in Chronic Stroke: A Pilot Study Toward an fNIRS-BCI for Gait Rehabilitation.
    Rea M; Rana M; Lugato N; Terekhin P; Gizzi L; Brötz D; Fallgatter A; Birbaumer N; Sitaram R; Caria A
    Neurorehabil Neural Repair; 2014 Jul; 28(6):564-75. PubMed ID: 24482298
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Preserved foot motor cortex in patients with complete spinal cord injury: a functional near-infrared spectroscopic study.
    Koenraadt KL; Duysens J; Rijken H; van Nes IJ; Keijsers NL
    Neurorehabil Neural Repair; 2014 Feb; 28(2):179-87. PubMed ID: 24213959
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Neuronal Activation Detection Using Vector Phase Analysis with Dual Threshold Circles: A Functional Near-Infrared Spectroscopy Study.
    Zafar A; Hong KS
    Int J Neural Syst; 2018 Dec; 28(10):1850031. PubMed ID: 30045647
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Computationally Efficient Method for Hybrid EEG-fNIRS BCI Based on the Pearson Correlation.
    Hasan MAH; Khan MU; Mishra D
    Biomed Res Int; 2020; 2020():1838140. PubMed ID: 32923476
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Synchronizing Motor Imagery Cue in fNIRS Brain-Computer Interface to reduce confounding effects of respiration.
    Premchand B; Zhang Z; Yu J; Yang T; Ang KK
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083697
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): Training of volitional wrist extension after stroke, a case series pilot study.
    Matarasso AK; Rieke JD; White K; Yusufali MM; Daly JJ
    PLoS One; 2021; 16(5):e0250431. PubMed ID: 33956845
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Speaking mode recognition from functional Near Infrared Spectroscopy.
    Herff C; Putze F; Heger D; Guan C; Schultz T
    Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():1715-8. PubMed ID: 23366240
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.
    Robinson N; Zaidi AD; Rana M; Prasad VA; Guan C; Birbaumer N; Sitaram R
    PLoS One; 2016; 11(7):e0159959. PubMed ID: 27467528
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.