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ENTITY fNIRS

fNIRS

PulseAugur coverage of fNIRS — every cluster mentioning fNIRS across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 7 TOTAL
  1. TOOL · CL_306656 ·

    GeoNIRS framework advances fNIRS data pretraining using geometry-aware approach

    Researchers have developed GeoNIRS, a novel framework for pretraining functional near-infrared spectroscopy (fNIRS) data. This geometry-aware approach uses source-detector locations to create a shared spatial reference,…

  2. TOOL · CL_228532 ·

    Non-invasive BCIs advance toward commercialization beyond EEG

    Non-invasive Brain-Computer Interfaces (BCIs) are progressing towards commercial viability, moving beyond traditional electroencephalography (EEG) methods. Neuracle is at the forefront of this advancement, particularly …

  3. TOOL · CL_193442 ·

    fNIRS-based autism classification benchmarked for temporal generalization

    A new research paper published on arXiv explores the challenges of using functional near-infrared spectroscopy (fNIRS) for autism spectrum disorder (ASD) classification. The study introduces a cross-time-window transfer…

  4. TOOL · CL_183417 ·

    New FRED system decodes imagined handwriting from EEG data

    Researchers have developed FRED, a system designed to decode imagined handwriting from EEG and fNIRS data. The system utilizes a temporal network that processes complementary EEG frequency views to model motor sequences…

  5. TOOL · CL_147938 ·

    fNIRS brain signals guide robot reinforcement learning

    Researchers have developed an offline approach to guide robot behavior using functional near-infrared spectroscopy (fNIRS) brain signals. This method integrates neural data into reinforcement learning algorithms, augmen…

  6. TOOL · CL_93355 ·

    EEGNet study reveals challenges in fNIRS-driven cognitive load classification

    A new study published on arXiv evaluates the effectiveness of EEGNet for classifying cognitive load using fNIRS signals. The research systematically examined various parameters, including temporal segmentation, window l…

  7. TOOL · CL_84861 ·

    New framework uses EEG and fNIRS to detect depressive states

    Researchers have developed a new framework for classifying depressive states using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) biological signals. This pilot study, involving eleven he…