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Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system
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:...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8765296/ https://www.ncbi.nlm.nih.gov/pubmed/35043610 http://dx.doi.org/10.1117/1.JBO.27.7.074710 |
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author | Ban, Han Y. Barrett, Geoffrey M. Borisevich, Alex Chaturvedi, Ashutosh Dahle, Jacob L. Dehghani, Hamid Dubois, Julien Field, Ryan M. Gopalakrishnan, Viswanath Gundran, Andrew Henninger, Michael Ho, Wilson C. Hughes, Howard D. Jin, Rong Kates-Harbeck, Julian Landy, Thanh Leggiero, Michael Lerner, Gabriel Aghajan, Zahra M. Moon, Michael Olvera, Isai Park, Sangyong Patel, Milin J. Perdue, Katherine L. Siepser, Benjamin Sorgenfrei, Sebastian Sun, Nathan Szczepanski, Victor Zhang, Mary Zhu, Zhenye |
author_facet | Ban, Han Y. Barrett, Geoffrey M. Borisevich, Alex Chaturvedi, Ashutosh Dahle, Jacob L. Dehghani, Hamid Dubois, Julien Field, Ryan M. Gopalakrishnan, Viswanath Gundran, Andrew Henninger, Michael Ho, Wilson C. Hughes, Howard D. Jin, Rong Kates-Harbeck, Julian Landy, Thanh Leggiero, Michael Lerner, Gabriel Aghajan, Zahra M. Moon, Michael Olvera, Isai Park, Sangyong Patel, Milin J. Perdue, Katherine L. Siepser, Benjamin Sorgenfrei, Sebastian Sun, Nathan Szczepanski, Victor Zhang, Mary Zhu, Zhenye |
author_sort | Ban, Han Y. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8765296 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-87652962022-01-20 Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system Ban, Han Y. Barrett, Geoffrey M. Borisevich, Alex Chaturvedi, Ashutosh Dahle, Jacob L. Dehghani, Hamid Dubois, Julien Field, Ryan M. Gopalakrishnan, Viswanath Gundran, Andrew Henninger, Michael Ho, Wilson C. Hughes, Howard D. Jin, Rong Kates-Harbeck, Julian Landy, Thanh Leggiero, Michael Lerner, Gabriel Aghajan, Zahra M. Moon, Michael Olvera, Isai Park, Sangyong Patel, Milin J. Perdue, Katherine L. Siepser, Benjamin Sorgenfrei, Sebastian Sun, Nathan Szczepanski, Victor Zhang, Mary Zhu, Zhenye J Biomed Opt Special Section on Tissue Phantoms to Advance Biomedical Optical Systems 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. Society of Photo-Optical Instrumentation Engineers 2022-01-18 2022-07 /pmc/articles/PMC8765296/ /pubmed/35043610 http://dx.doi.org/10.1117/1.JBO.27.7.074710 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/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. |
spellingShingle | Special Section on Tissue Phantoms to Advance Biomedical Optical Systems Ban, Han Y. Barrett, Geoffrey M. Borisevich, Alex Chaturvedi, Ashutosh Dahle, Jacob L. Dehghani, Hamid Dubois, Julien Field, Ryan M. Gopalakrishnan, Viswanath Gundran, Andrew Henninger, Michael Ho, Wilson C. Hughes, Howard D. Jin, Rong Kates-Harbeck, Julian Landy, Thanh Leggiero, Michael Lerner, Gabriel Aghajan, Zahra M. Moon, Michael Olvera, Isai Park, Sangyong Patel, Milin J. Perdue, Katherine L. Siepser, Benjamin Sorgenfrei, Sebastian Sun, Nathan Szczepanski, Victor Zhang, Mary Zhu, Zhenye Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title | Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title_full | Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title_fullStr | Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title_full_unstemmed | Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title_short | Kernel Flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
title_sort | kernel flow: a high channel count scalable time-domain functional near-infrared spectroscopy system |
topic | Special Section on Tissue Phantoms to Advance Biomedical Optical Systems |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8765296/ https://www.ncbi.nlm.nih.gov/pubmed/35043610 http://dx.doi.org/10.1117/1.JBO.27.7.074710 |
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