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 *

173 related articles for article (PubMed ID: 33307543)

  • 1. Unsupervised fNIRS feature extraction with CAE and ESN autoencoder for driver cognitive load classification.
    Liu R; Reimer B; Song S; Mehler B; Solovey E
    J Neural Eng; 2021 Mar; 18(3):. PubMed ID: 33307543
    [No Abstract]   [Full Text] [Related]  

  • 2. Functional near-infrared spectroscopy in the evaluation of urban rail transit drivers' mental workload under simulated driving conditions.
    Li LP; Liu ZG; Zhu HY; Zhu L; Huang YC
    Ergonomics; 2019 Mar; 62(3):406-419. PubMed ID: 30307379
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Load-dependent relationships between frontal fNIRS activity and performance: A data-driven PLS approach.
    Meidenbauer KL; Choe KW; Cardenas-Iniguez C; Huppert TJ; Berman MG
    Neuroimage; 2021 Apr; 230():117795. PubMed ID: 33503483
    [TBL] [Abstract][Full Text] [Related]  

  • 5. K-Means Clustering Machine Learning Approach Reveals Groups of Homogeneous Individuals With Unique Brain Activation, Task, and Performance Dynamics Using fNIRS.
    Saikia MJ
    IEEE Trans Neural Syst Rehabil Eng; 2023; 31():2535-2544. PubMed ID: 37216239
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Enhancing classification accuracy of fNIRS-BCI using features acquired from vector-based phase analysis.
    Nazeer H; Naseer N; Khan RA; Noori FM; Qureshi NK; Khan US; Khan MJ
    J Neural Eng; 2020 Oct; 17(5):056025. PubMed ID: 33055382
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Diagnosis of Mild Cognitive Impairment Using Cognitive Tasks: A Functional Near-Infrared Spectroscopy Study.
    Yoo SH; Woo SW; Shin MJ; Yoon JA; Shin YI; Hong KS
    Curr Alzheimer Res; 2020; 17(13):1145-1160. PubMed ID: 33583382
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classifying Drivers' Cognitive Load Using EEG Signals.
    Barua S; Ahmed MU; Begum S
    Stud Health Technol Inform; 2017; 237():99-106. PubMed ID: 28479551
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An EEG-fNIRS hybridization technique in the four-class classification of alzheimer's disease.
    Cicalese PA; Li R; Ahmadi MB; Wang C; Francis JT; Selvaraj S; Schulz PE; Zhang Y
    J Neurosci Methods; 2020 Apr; 336():108618. PubMed ID: 32045572
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic Cognitive Fatigue Detection Using Wearable fNIRS and Machine Learning.
    Varandas R; Lima R; Bermúdez I Badia S; Silva H; Gamboa H
    Sensors (Basel); 2022 May; 22(11):. PubMed ID: 35684626
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Transformer Model for Functional Near-Infrared Spectroscopy Classification.
    Wang Z; Zhang J; Zhang X; Chen P; Wang B
    IEEE J Biomed Health Inform; 2022 Jun; 26(6):2559-2569. PubMed ID: 34986110
    [TBL] [Abstract][Full Text] [Related]  

  • 12. CNN-based classification of fNIRS signals in motor imagery BCI system.
    Ma T; Wang S; Xia Y; Zhu X; Evans J; Sun Y; He S
    J Neural Eng; 2021 Apr; 18(5):. PubMed ID: 33761480
    [No Abstract]   [Full Text] [Related]  

  • 13. Analyzing Classification Performance of fNIRS-BCI for Gait Rehabilitation Using Deep Neural Networks.
    Hamid H; Naseer N; Nazeer H; Khan MJ; Khan RA; Shahbaz Khan U
    Sensors (Basel); 2022 Mar; 22(5):. PubMed ID: 35271077
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Multimodal Autoencoder Predicts fNIRS Resting State From EEG Signals.
    Sirpal P; Damseh R; Peng K; Nguyen DK; Lesage F
    Neuroinformatics; 2022 Jul; 20(3):537-558. PubMed ID: 34378155
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessing the Driver's Current Level of Working Memory Load with High Density Functional Near-infrared Spectroscopy: A Realistic Driving Simulator Study.
    Unni A; Ihme K; Jipp M; Rieger JW
    Front Hum Neurosci; 2017; 11():167. PubMed ID: 28424602
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Exploring fNIRS-Based Brain State Recognition and Visualization through the use of Explainable Convolutional Neural Networks.
    Chen PH; Wei CS; Lan CC; Chen NF; Wang LC
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38082873
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Classification of Individual Finger Movements from Right Hand Using fNIRS Signals.
    Khan H; Noori FM; Yazidi A; Uddin MZ; Khan MNA; Mirtaheri P
    Sensors (Basel); 2021 Nov; 21(23):. PubMed ID: 34883949
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A General and Scalable Vision Framework for Functional Near-Infrared Spectroscopy Classification.
    Wang Z; Zhang J; Xia Y; Chen P; Wang B
    IEEE Trans Neural Syst Rehabil Eng; 2022; 30():1982-1991. PubMed ID: 35830404
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 9.