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Related Experiment Video

Updated: Oct 2, 2025

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Identifying Individuals by fNIRS-Based Brain Functional Network Fingerprints.

Haonan Ren1, Shufeng Zhou1, Limei Zhang1

  • 1School of Mathematics Science, Liaocheng University, Liaocheng, China.

Frontiers in Neuroscience
|February 28, 2022
PubMed
Summary
This summary is machine-generated.

Functional near-infrared spectroscopy (fNIRS) can identify individuals using brain functional networks (BFNs). BFN fingerprints derived from fNIRS data show potential as a novel biometric for identity authentication.

Keywords:
brain functional network (BFN)cross-taskcross-viewfunctional near-infrared spectroscopyindividual identification

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Area of Science:

  • Neuroscience
  • Biometrics
  • Signal Processing

Background:

  • Individual identification using brain functional networks (BFNs) is a growing research area.
  • Previous studies utilized fMRI, EEG, and MEG for BFN-based identification.
  • Functional near-infrared spectroscopy (fNIRS) offers a novel, non-invasive approach to measure cerebral activity.

Purpose of the Study:

  • To investigate the feasibility of using fNIRS-based BFNs as a biometric for individual identification.
  • To determine if fNIRS-derived BFNs can serve as a unique 'fingerprint' for individuals.
  • To compare identification accuracy across different tasks and signal types (oxyhemoglobin vs. de-oxyhemoglobin).

Main Methods:

  • Calculated BFNs using Pearson's correlation on preprocessed fNIRS signals.
  • Employed a nearest neighbor scheme for matching BFNs between individuals.
  • Utilized an open-access fNIRS dataset for experimental validation.

Main Results:

  • BFN fingerprints derived from fNIRS demonstrated effective individual identification across various tasks (resting, finger tapping, foot tapping).
  • Identification accuracy was significantly higher under cross-task conditions compared to cross-view conditions (oxyhemoglobin vs. de-oxyhemoglobin).
  • These findings suggest robustness of fNIRS-based BFNs for distinguishing individuals.

Conclusions:

  • fNIRS-based BFNs show promise as a novel biometric for individual identification.
  • The BFN fingerprint derived from fNIRS is a feasible and potentially accurate method for identity authentication.
  • Further research can explore the application of fNIRS in biometric systems.