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Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface.

Publication ,  Conference
Shull, G; Shin, Y; Viventi, J; Jochum, T; Morizio, J; Seo, KJ; Fang, H
Published in: IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference
October 2022

Brain computer interfaces (BCIs) provide clinical benefits including partial restoration of lost motor control, vision, speech, and hearing. A fundamental limitation of existing BCIs is their inability to span several areas (> cm2) of the cortex with fine (<100 μm) resolution. One challenge of scaling neural interfaces is output wiring and connector sizes as each channel must be independently routed out of the brain. Time division multiplexing (TDM) overcomes this by enabling several channels to share the same output wire at the cost of added noise. This work leverages a 130-nm CMOS process and transfer printing to design and simulate a 384-channel actively multiplexed array, which minimizes noise by adding front end filtering and amplification to every electrode site (pixel). The pixels are 50 μm × 50 μm and enable recording of all 384 channels at 30 kHz with a gain of 22.3 dB, noise of 9.57 μV rms, bandwidth of 0.1 Hz - 10 kHz, while only consuming 0.63 μW/channel. This work can be applied broadly across neural interfaces to create high channel-count arrays and ultimately improve BCIs.

Duke Scholars

Published In

IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference

DOI

Publication Date

October 2022

Volume

2022

Start / End Page

477 / 481
 

Citation

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Shull, G., Shin, Y., Viventi, J., Jochum, T., Morizio, J., Seo, K. J., & Fang, H. (2022). Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface. In IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference (Vol. 2022, pp. 477–481). https://doi.org/10.1109/biocas54905.2022.9948553
Shull, Gabriella, Yieljae Shin, Jonathan Viventi, Thomas Jochum, James Morizio, Kyung Jin Seo, and Hui Fang. “Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface.” In IEEE Biomedical Circuits and Systems Conference : Healthcare Technology : [Proceedings]. IEEE Biomedical Circuits and Systems Conference, 2022:477–81, 2022. https://doi.org/10.1109/biocas54905.2022.9948553.
Shull G, Shin Y, Viventi J, Jochum T, Morizio J, Seo KJ, et al. Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface. In: IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings] IEEE Biomedical Circuits and Systems Conference. 2022. p. 477–81.
Shull, Gabriella, et al. “Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface.IEEE Biomedical Circuits and Systems Conference : Healthcare Technology : [Proceedings]. IEEE Biomedical Circuits and Systems Conference, vol. 2022, 2022, pp. 477–81. Epmc, doi:10.1109/biocas54905.2022.9948553.
Shull G, Shin Y, Viventi J, Jochum T, Morizio J, Seo KJ, Fang H. Design and Simulation of a Low Power 384-channel Actively Multiplexed Neural Interface. IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings] IEEE Biomedical Circuits and Systems Conference. 2022. p. 477–481.

Published In

IEEE Biomedical Circuits and Systems Conference : healthcare technology : [proceedings]. IEEE Biomedical Circuits and Systems Conference

DOI

Publication Date

October 2022

Volume

2022

Start / End Page

477 / 481