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Related Concept Videos

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences01:17

NMR Spectrometers: Radiofrequency Pulses and Pulse Sequences

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A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
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NMR Spectrometers: Overview01:20

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NMR spectrometers consist of a strong magnet, a radiofrequency transmitter, and a detector attached to a computer console for recording spectra of samples containing NMR-active nuclei. In first-generation NMR instruments called continuous-wave spectrometers, the resonance frequencies of the nuclei are determined by frequency-sweep or field-sweep methods. The magnetic field strength is fixed and the rf signal is swept in the former, while the radiofrequency signal is fixed and the magnetic field...
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Related Experiment Video

Updated: Oct 10, 2025

Simultaneous Data Collection of fMRI and fNIRS Measurements Using a Whole-Head Optode Array and Short-Distance Channels
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A practical guide for synthetic fNIRS data generation.

Jessica Gemignani, Judit Gervain

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 11, 2021
    PubMed
    Summary
    This summary is machine-generated.

    Researchers can now objectively validate functional near-infrared spectroscopy (fNIRS) analysis methods using a large, diverse synthetic dataset. This work details the data generation process and provides accessible tools for creating the dataset.

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    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique.
    • Objective validation of fNIRS data analysis methods is crucial for reliable research outcomes.
    • Existing datasets may lack the diversity and ground-truth necessary for comprehensive validation.

    Purpose of the Study:

    • To introduce a large and diversified ground-truth synthetic fNIRS dataset.
    • To enable objective validation and comparison of fNIRS data analysis procedures.
    • To provide researchers with tools for generating this synthetic dataset.

    Main Methods:

    • Detailed description of the synthetic data generation workflow.
    • Implementation of algorithms for creating diverse fNIRS signal patterns.
    • Inclusion of ground-truth labels for simulated physiological and artifactual signals.

    Main Results:

    • A comprehensive synthetic fNIRS dataset is now available.
    • The dataset facilitates the objective benchmarking of various fNIRS analysis techniques.
    • The provided tools allow for reproducible dataset generation.

    Conclusions:

    • The availability of this synthetic dataset significantly advances the field of fNIRS research.
    • Objective validation is now more accessible, promoting higher quality research.
    • This resource empowers researchers to rigorously assess and improve their analysis pipelines.