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@inproceedings{Ahmadi:2019:10.1109/NER.2019.8716998,
author = {Ahmadi, N and Cavuto, ML and Feng, P and Leene, LB and Maslik, M and Mazza, F and Savolainen, O and Szostak, KM and Bouganis, C-S and Ekanayake, J and Jackson, A and Constandinou, TG},
doi = {10.1109/NER.2019.8716998},
pages = {719--724},
publisher = {IEEE},
title = {Towards a distributed, chronically-implantable neural interface},
url = {http://dx.doi.org/10.1109/NER.2019.8716998},
year = {2019}
}

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TY  - CPAPER
AB  - We present a platform technology encompassing a family of innovations that together aim to tackle key challenges with existing implantable brain machine interfaces. The ENGINI (Empowering Next Generation Implantable Neural Interfaces) platform utilizes a 3-tier network (external processor, cranial transponder, intracortical probes) to inductively couple power to, and communicate data from, a distributed array of freely-floating mm-scale probes. Novel features integrated into each probe include: (1) an array of niobium microwires for observing local field potentials (LFPs) along the cortical column; (2) ultra-low power instrumentation for signal acquisition and data reduction; (3) an autonomous, self-calibrating wireless transceiver for receiving power and transmitting data; and (4) a hermetically-sealed micropackage suitable for chronic use. We are additionally engineering a surgical tool, to facilitate manual and robot-assisted insertion, within a streamlined neurosurgical workflow. Ongoing work is focused on system integration and preclinical testing.
AU  - Ahmadi,N
AU  - Cavuto,ML
AU  - Feng,P
AU  - Leene,LB
AU  - Maslik,M
AU  - Mazza,F
AU  - Savolainen,O
AU  - Szostak,KM
AU  - Bouganis,C-S
AU  - Ekanayake,J
AU  - Jackson,A
AU  - Constandinou,TG
DO  - 10.1109/NER.2019.8716998
EP  - 724
PB  - IEEE
PY  - 2019///
SN  - 1948-3546
SP  - 719
TI  - Towards a distributed, chronically-implantable neural interface
UR  - http://dx.doi.org/10.1109/NER.2019.8716998
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000469933200175&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/66948
ER  -

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