Collage of published research papers

Citation

BibTex format

@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}
}

RIS format (EndNote, RefMan)

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 -

Awards

  • Finalist: Best Paper - IEEE Transactions on Mechatronics (awarded June 2021)

  • Finalist: IEEE Transactions on Mechatronics; 1 of 5 finalists for Best Paper in Journal

  • Winner: UK Institute of Mechanical Engineers (IMECHE) Healthcare Technologies Early Career Award (awarded June 2021): Awarded to Maria Lima (UKDRI CR&T PhD candidate)

  • Winner: Sony Start-up Acceleration Program (awarded May 2021): Spinout company Serg Tech awarded (1 of 4 companies in all of Europe) a place in Sony corporation start-up boot camp

  • “An Extended Complementary Filter for Full-Body MARG Orientation Estimation” (CR&T authors: S Wilson, R Vaidyanathan)

UK DRI


Established in 2017 by its principal funder the Medical Research Council, in partnership with Alzheimer's Society and Alzheimer’s Research UK, The UK Dementia Research Institute (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.