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

Authors :
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
Source :
Journal of Biomedical Optics
Publication Year :
2022
Publisher :
SPIE-Intl Soc Optical Eng, 2022.

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.

Details

ISSN :
10833668
Volume :
27
Database :
OpenAIRE
Journal :
Journal of Biomedical Optics
Accession number :
edsair.doi.dedup.....bd3584bb90b1c4320d58b07f808dc97d
Full Text :
https://doi.org/10.1117/1.jbo.27.7.074710