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Related Experiment Video

Updated: Apr 14, 2026

Proton Transfer and Protein Conformation Dynamics in Photosensitive Proteins by Time-resolved Step-scan Fourier-transform Infrared Spectroscopy
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Highly parallel, 1060 nm interferometric diffusing wave spectroscopy with a time-of-flight filter.

Santosh Aparanji1,2, Mingjun Zhao1,2, Akshay Shashidhar Nadig1

  • 1Tech4Health Institute, NYU Langone Health, New York, New York 11101, USA.

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|April 13, 2026
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Summary
This summary is machine-generated.

Interferometric diffuse optics (iDO) using near-infrared light monitors brain signals. This study demonstrates a new system for high-speed cerebral blood flow index (BFI) monitoring, improving signal depth and quality.

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Area of Science:

  • Biomedical Optics
  • Neuroimaging
  • Photonics

Background:

  • Near-infrared (NIR) light technologies like interferometric diffuse optics (iDO) are emerging for brain signal monitoring.
  • Coherent light fluctuations are key indicators of brain activity.
  • Cerebral blood flow index (BFI) monitoring requires high-speed and accurate measurements.

Purpose of the Study:

  • To demonstrate a line scan interferometric diffusing wave spectroscopy (iDWS) system at 1060 nm for BFI monitoring.
  • To evaluate the system's performance on subjects with varying skin types and hair.
  • To implement and assess a time-of-flight (TOF) filter for depth-resolved measurements.

Main Methods:

  • Developed a line scan iDWS system operating at 1060 nm.
  • Performed pulsatile BFI measurements on human subjects (Fitzpatrick Type V).
  • Integrated an electronically tunable time-of-flight (TOF) filter using source wavelength tuning.

Main Results:

  • Successfully demonstrated BFI measurements up to 5.5 cm source-collector separation.
  • The TOF filter reduced scalp sensitivity by 2.92-fold at 4 cm separation compared to continuous wave (CW) mode.
  • The system showed potential for high-throughput neuromonitoring.

Conclusions:

  • The 1060 nm iDWS system with TOF filtering shows promise for improved depth sensitivity in neuromonitoring.
  • This technology can enhance signal-to-noise ratio for brain signal analysis.
  • Further optimization could lead to advanced non-invasive brain monitoring applications.