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Published on: November 8, 2019
Scalable, modular continuous wave functional near-infrared spectroscopy system (Spotlight).
Daniel Anaya1, Gautam Batra1, Peter Bracewell1
1Meta Platforms, Inc., Menlo Park, California, United States.
We developed Spotlight, a portable functional near-infrared spectroscopy (fNIRS) system for brain-computer interfaces (BCI). This modular device achieved high accuracy in decoding finger-tapping tasks, enhancing non-invasive neuroscience research.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique.
- Existing fNIRS devices can be bulky and lack portability, limiting their application in real-world scenarios.
- Advancements in portable and modular fNIRS systems are crucial for expanding neuroscience and brain-computer interface (BCI) research.
Purpose of the Study:
- To introduce Spotlight, a novel fiberless, portable, and modular continuous wave-functional near-infrared spectroscopy (fNIRS) system.
- To enhance the accessibility and power of fNIRS devices for neuroscience and BCI applications.
- To provide designs that can foster further innovation in fNIRS technology.
Main Methods:
- Developed a modular fNIRS system (Spotlight) with palm-sized modules containing high-density LED and silicon photomultiplier detector arrays.
- Embedded optoelectronic components in a flexible membrane for optimal scalp coupling.
- Validated system performance using phantoms and conducted a human finger-tapping experiment with custom 3D-printed caps.
Main Results:
- Demonstrated sensor characteristics through phantom validation.
- Successfully captured motor cortical hemodynamic responses during a finger-tapping task in human subjects.
- Achieved offline decoding accuracy of median 69.6% (up to 94.7%) for task conditions, with comparable real-time accuracy.
- Observed a correlation between custom cap fit, hemodynamic response magnitude, and decoding accuracy.
Conclusions:
- Spotlight represents a significant step towards more accessible and powerful fNIRS systems.
- The modular and portable design facilitates broader application in BCI research.
- Improved cap fit enhances the quality of neuroimaging data and decoding performance in fNIRS studies.
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