Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system

Han Y. Ban; Geoffrey M. Barrett; Alex Borisevich; Ashutosh Chaturvedi; Jacob L. Dahle; Hamid Dehghani; Julien Dubois; Ryan M. Field; Viswanath Gopalakrishnan; Andrew Gundran; Michael Henninger; Wilson C. Ho; Howard D. Hughes; Rong Jin; Julian Kates-Harbeck; Thanh Landy; Michael Leggiero; Gabriel Lerner; Zahra M. Aghajan; Michael Moon; Isai Olvera; Sangyong Park; Milin J. Patel; Katherine L. Perdue; Benjamin Siepser; Sebastian Sorgenfrei; Nathan Sun; Victor Szczepanski; Mary Zhang; Zhenye Zhu

doi:10.1117/1.JBO.27.7.074710

Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system

Han Y. Ban, Geoffrey M. Barrett, Alex Borisevich, Ashutosh Chaturvedi, Jacob L. Dahle, Hamid Dehghani, Julien Dubois, Ryan M. Field^*, Viswanath Gopalakrishnan, Andrew Gundran, Michael Henninger, Wilson C. Ho, Howard D. Hughes, Rong Jin, Julian Kates-Harbeck, Thanh Landy, Michael Leggiero, Gabriel Lerner, Zahra M. Aghajan, Michael MoonIsai Olvera, Sangyong Park, Milin J. Patel, Katherine L. Perdue, Benjamin Siepser, Sebastian Sorgenfrei, Nathan Sun, Victor Szczepanski, Mary Zhang, Zhenye Zhu

^*Corresponding author for this work

Computer Science

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Abstract

Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems.

Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device.

Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head.

Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results.

Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.

Original language	English
Article number	074710
Journal	Journal of Biomedical Optics
Volume	27
Issue number	7
DOIs	https://doi.org/10.1117/1.JBO.27.7.074710
Publication status	Published - 18 Jan 2022

Bibliographical note

Funding Information:
This work was supported by Kernel.

Publisher Copyright:
© The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Keywords

functional near-infrared spectroscopy
optical brain imaging
optical properties
single-photon detectors
time-resolved spectroscopy
tissue optics

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Biomaterials
Atomic and Molecular Physics, and Optics
Biomedical Engineering

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BanH2022KernelFinal published version, 7.13 MBLicence: Creative Commons: Attribution (CC BY)

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Ban, H. Y., Barrett, G. M., Borisevich, A., Chaturvedi, A., Dahle, J. L., Dehghani, H., Dubois, J., Field, R. M., Gopalakrishnan, V., Gundran, A., Henninger, M., Ho, W. C., Hughes, H. D., Jin, R., Kates-Harbeck, J., Landy, T., Leggiero, M., Lerner, G., Aghajan, Z. M., ... Zhu, Z. (2022). Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system. Journal of Biomedical Optics, 27(7), Article 074710. https://doi.org/10.1117/1.JBO.27.7.074710

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title = "Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system",

abstract = "Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.",

keywords = "functional near-infrared spectroscopy, optical brain imaging, optical properties, single-photon detectors, time-resolved spectroscopy, tissue optics",

author = "Ban, {Han Y.} and Barrett, {Geoffrey M.} and Alex Borisevich and Ashutosh Chaturvedi and Dahle, {Jacob L.} and Hamid Dehghani and Julien Dubois and Field, {Ryan M.} and Viswanath Gopalakrishnan and Andrew Gundran and Michael Henninger and Ho, {Wilson C.} and Hughes, {Howard D.} and Rong Jin and Julian Kates-Harbeck and Thanh Landy and Michael Leggiero and Gabriel Lerner and Aghajan, {Zahra M.} and Michael Moon and Isai Olvera and Sangyong Park and Patel, {Milin J.} and Perdue, {Katherine L.} and Benjamin Siepser and Sebastian Sorgenfrei and Nathan Sun and Victor Szczepanski and Mary Zhang and Zhenye Zhu",

note = "Funding Information: This work was supported by Kernel. Publisher Copyright: {\textcopyright} The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.",

year = "2022",

month = jan,

day = "18",

doi = "10.1117/1.JBO.27.7.074710",

language = "English",

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Ban, HY, Barrett, GM, Borisevich, A, Chaturvedi, A, Dahle, JL, Dehghani, H, Dubois, J, Field, RM, Gopalakrishnan, V, Gundran, A, Henninger, M, Ho, WC, Hughes, HD, Jin, R, Kates-Harbeck, J, Landy, T, Leggiero, M, Lerner, G, Aghajan, ZM, Moon, M, Olvera, I, Park, S, Patel, MJ, Perdue, KL, Siepser, B, Sorgenfrei, S, Sun, N, Szczepanski, V, Zhang, M & Zhu, Z 2022, 'Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system', Journal of Biomedical Optics, vol. 27, no. 7, 074710. https://doi.org/10.1117/1.JBO.27.7.074710

TY - JOUR

T1 - Kernel Flow

T2 - a high channel count scalable time-domain functional near-infrared spectroscopy system

AU - Ban, Han Y.

AU - Barrett, Geoffrey M.

AU - Borisevich, Alex

AU - Chaturvedi, Ashutosh

AU - Dahle, Jacob L.

AU - Dehghani, Hamid

AU - Dubois, Julien

AU - Field, Ryan M.

AU - Gopalakrishnan, Viswanath

AU - Gundran, Andrew

AU - Henninger, Michael

AU - Ho, Wilson C.

AU - Hughes, Howard D.

AU - Jin, Rong

AU - Kates-Harbeck, Julian

AU - Landy, Thanh

AU - Leggiero, Michael

AU - Lerner, Gabriel

AU - Aghajan, Zahra M.

AU - Moon, Michael

AU - Olvera, Isai

AU - Park, Sangyong

AU - Patel, Milin J.

AU - Perdue, Katherine L.

AU - Siepser, Benjamin

AU - Sorgenfrei, Sebastian

AU - Sun, Nathan

AU - Szczepanski, Victor

AU - Zhang, Mary

AU - Zhu, Zhenye

N1 - Funding Information: This work was supported by Kernel. Publisher Copyright: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

PY - 2022/1/18

Y1 - 2022/1/18

N2 - Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.

AB - Significance: Time-domain functional near-infrared spectroscopy (TD-fNIRS) has been considered as the gold standard of noninvasive optical brain imaging devices. However, due to the high cost, complexity, and large form factor, it has not been as widely adopted as continuous wave NIRS systems. Aim: Kernel Flow is a TD-fNIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-fNIRS system while integrating all of the components into a small modular device. Approach: The Kernel Flow modules are built around miniaturized laser drivers, custom integrated circuits, and specialized detectors. The modules can be assembled into a system with dense channel coverage over the entire head. Results: We show performance similar to benchtop systems with our miniaturized device as characterized by standardized tissue and optical phantom protocols for TD-fNIRS and human neuroscience results. Conclusions: The miniaturized design of the Kernel Flow system allows for broader applications of TD-fNIRS.

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KW - optical properties

KW - single-photon detectors

KW - time-resolved spectroscopy

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Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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