Kernel flow: a high channel count scalable TD-fNIRS system

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

doi:10.1117/12.2582888

5 March 2021 Kernel flow: a high channel count scalable TD-fNIRS system

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

Author Affiliations +

Proceedings Volume 11663, Integrated Sensors for Biological and Neural Sensing; 116630B (2021) https://doi.org/10.1117/12.2582888
Event: SPIE BiOS, 2021, Online Only

Abstract

Time-Domain Near-Infrared Spectroscopy (TD-NIRS) has been considered as the gold standard of non-invasive 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 (CW) NIRS systems. Kernel Flow is a TD-NIRS system that has been designed to break through these limitations by maintaining the performance of a research grade TD-NIRS system while integrating all of the components into a small modular device. 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. We show performance similar to benchtop systems with our miniaturized device.

Conference Presentation

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Han Y. Ban, Geoffrey M. Barrett, Alex Borisevich, Ashutosh Chaturvedi, Jacob L. Dahle, Hamid Dehghani, Bruno DoValle, Julien Dubois, Ryan M. Field, Viswanath Gopalakrishnan, Andrew Gundran, Michael Henninger, Wilson C. Ho, Howard D. Hughes, Rong Jin, Julian Kates-Harbeck, Thanh Landy, Antonio H. Lara, Michael Leggiero, Gabriel Lerner, Zahra M. Aghajan, Michael Moon, Alejandro Ojeda, Isai Olvera, Meric Ozturk, Sangyong Park, Milin J. Patel, Katherine L. Perdue, Wing Poon, Zachary P. Sheldon, Benjamin Siepser, Sebastian Sorgenfrei, Nathan Sun, Victor Szczepanski, Mary Zhang, and Zhenye Zhu "Kernel flow: a high channel count scalable TD-fNIRS system", Proc. SPIE 11663, Integrated Sensors for Biological and Neural Sensing, 116630B (5 March 2021); https://doi.org/10.1117/12.2582888

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