Origami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography
Lawrence Coles,
Domenico Ventrella,
Alejandro Carnicer-Lombarte,
Alberto Elmi,
Joe G. Troughton,
Massimo Mariello,
Salim El Hadwe,
Ben J. Woodington,
Maria L. Bacci,
George G. Malliaras,
Damiano G. Barone and
Christopher M. Proctor ()
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Lawrence Coles: University of Cambridge
Domenico Ventrella: University of Bologna
Alejandro Carnicer-Lombarte: University of Cambridge
Alberto Elmi: University of Bologna
Joe G. Troughton: University of Cambridge
Massimo Mariello: University of Oxford
Salim El Hadwe: University of Cambridge
Ben J. Woodington: University of Cambridge
Maria L. Bacci: University of Bologna
George G. Malliaras: University of Cambridge
Damiano G. Barone: University of Cambridge
Christopher M. Proctor: University of Cambridge
Nature Communications, 2024, vol. 15, issue 1, 1-11
Abstract:
Abstract Electrocorticography is an established neural interfacing technique wherein an array of electrodes enables large-area recording from the cortical surface. Electrocorticography is commonly used for seizure mapping however the implantation of large-area electrocorticography arrays is a highly invasive procedure, requiring a craniotomy larger than the implant area to place the device. In this work, flexible thin-film electrode arrays are combined with concepts from soft robotics, to realize a large-area electrocorticography device that can change shape via integrated fluidic actuators. We show that the 32-electrode device can be packaged using origami-inspired folding into a compressed state and implanted through a small burr-hole craniotomy, then expanded on the surface of the brain for large-area cortical coverage. The implantation, expansion, and recording functionality of the device is confirmed in-vitro and in porcine in-vivo models. The integration of shape actuation into neural implants provides a clinically viable pathway to realize large-area neural interfaces via minimally invasive surgical techniques.
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-50597-2
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DOI: 10.1038/s41467-024-50597-2
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