Scalable, modular continuous wave functional near-infrared spectroscopy system (Spotlight)

We present a fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy system, Spotlight, consisting of multiple palm-sized modules-each containing high-density light-emitting diode and silicon photomultiplier detector arrays embedded in a flexible membrane that facilita...

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Bibliographic Details
Published in:Journal of biomedical optics Vol. 28; no. 6; p. 065003
Main Authors: Anaya, Daniel, Batra, Gautam, Bracewell, Peter, Catoen, Ryan, Chakraborty, Dev, Chevillet, Mark, Damodara, Pradeep, Dominguez, Alvin, Emms, Laurence, Jiang, Zifan, Kim, Ealgoo, Klumb, Keith, Lau, Frances, Le, Rosemary, Li, Jamie, Mateo, Brett, Matloff, Laura, Mehta, Asha, Mugler, Emily M., Murthy, Akansh, Nakagome, Sho, Orendorff, Ryan, Saung, E-Fann, Schwarz, Roland, Sethi, Ruben, Sevile, Rudy, Srivastava, Ajay, Sundberg, John, Yang, Ying, Yin, Allen
Format: Journal Article
Language:English
Published: United States Society of Photo-Optical Instrumentation Engineers 01-06-2023
S P I E - International Society for
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Summary:We present a fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy system, Spotlight, consisting of multiple palm-sized modules-each containing high-density light-emitting diode and silicon photomultiplier detector arrays embedded in a flexible membrane that facilitates optode coupling to scalp curvature. Spotlight's goal is to be a more portable, accessible, and powerful functional near-infrared spectroscopy (fNIRS) device for neuroscience and brain-computer interface (BCI) applications. We hope that the Spotlight designs we share here can spur more advances in fNIRS technology and better enable future non-invasive neuroscience and BCI research. We report sensor characteristics in system validation on phantoms and motor cortical hemodynamic responses in a human finger-tapping experiment, where subjects wore custom 3D-printed caps with two sensor modules. The task conditions can be decoded offline with a median accuracy of 69.6%, reaching 94.7% for the best subject, and at a comparable accuracy in real time for a subset of subjects. We quantified how well the custom caps fitted to each subject and observed that better fit leads to more observed task-dependent hemodynamic response and better decoding accuracy. The advances presented here should serve to make fNIRS more accessible for BCI applications.
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These authors contributed equally to this work.
ISSN:1083-3668
1560-2281
DOI:10.1117/1.JBO.28.6.065003