Evidence map›Paper›PMID 39194613›Full record

ArticleBiosensors2024

A Device-on-Chip Solution for Real-Time Diffuse Correlation Spectroscopy Using FPGA.

Christopher H Moore, Ulas Sunar, Wei Lin

Abstract read
In one paragraph

Article in Biosensors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Christopher H MooreDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-6947-3960
Ulas SunarDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-0623-7522
Wei LinDepartment of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.ORCID 0000-0002-7265-2679

Funding

Quantitative Diffuse Correlation Spectroscopy for Assessing Human Brain FunctionR01EB031759 · NIBIB · WRIGHT STATE UNIVERSITY · PI SUNAR, ULAS · 2021 to 2022
$723k
NIBIB NIH HHS R01 EB031759NIH HHS 5R01EB031759-02
6 · The paper itself

Abstract

Diffuse correlation spectroscopy (DCS) is a non-invasive technology for the evaluation of blood perfusion in deep tissue. However, it requires high computational resources for data analysis, which poses challenges in its implementation for real-time applications. To address the unmet need, we developed a novel device-on-chip solution that fully integrates all the necessary computational components needed for DCS. It takes the output of a photon detector and determines the blood flow index (BFI). It is implemented on a field-programmable gate array (FPGA) chip including a multi-tau correlator for the calculation of the temporal light intensity autocorrelation function and a DCS analyzer to perform the curve fitting operation that derives the BFI at a rate of 6000 BFIs/s. The FPGA DCS system was evaluated against a lab-standard DCS system for both phantom and cuff ischemia studies. The results indicate that the autocorrelation of the light correlation and BFI from both the FPGA DCS and the reference DCS matched well. Furthermore, the FPGA DCS system was able to achieve a measurement rate of 50 Hz and resolve pulsatile blood flow. This can significantly lower the cost and footprint of the computational components of DCS and pave the way for portable, real-time DCS systems.

Indexed as

Spectrum AnalysisBiosensing TechniquesEquipment DesignHumansLab-On-A-Chip Devicesdevice-on-chipdiffuse correlation spectroscopyFPGAFPGA correlator

Identifiers

PMID39194613
PMCPMC11352433

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.