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A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS

Uran, Arda and Ture, Kerim and Aprile, Cosimo and Trouillet, Alix and Fallegger, Florian and Emami, Azita and Lacour, Stephanie P. and Dehollain, Catherine and Leblebici, Yusuf and Cevher, Volkan (2021) A 16-Channel Wireless Neural Recording System-on-Chip with CHT Feature Extraction Processor in 65nm CMOS. In: 2021 IEEE Custom Integrated Circuits Conference (CICC). IEEE , Piscataway, NJ, Art. No. 10-4. ISBN 9781728175812. https://resolver.caltech.edu/CaltechAUTHORS:20210528-094923310

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Abstract

Wireless implantable neural recording chips enable multichannel data acquisition with high spatiotemporal resolution in situ. Recently, the use of machine learning approaches on neural data for diagnosis and prosthesis control have renewed the interest in this field, and increased even more the demand for multichannel data. However, simultaneous data acquisition from many channels is a grand challenge due to data rate and power limitations on wireless transmission for implants. As a result, recent studies have focused on on-chip classifiers (Fig. 1 top), despite the fact that only primitive classifiers can be placed on resource-constrained chips. Moreover, robustness of the chosen algorithm cannot be guaranteed pre-implantation due to the scarcity of patient-specific data; waveforms can change over time due to electrode micro migration or tissue reaction, highlighting the need for robust adaptive features.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/cicc51472.2021.9431458DOIArticle
ORCID:
AuthorORCID
Uran, Arda0000-0002-8762-4494
Emami, Azita0000-0003-2608-9691
Additional Information:© 2021 IEEE. All animal experiments were approved by the Veterinary Office of the canton of Geneva in Switzerland and were in compliance with all relevant ethical regulations under animal license no GE 174_17. This work was supported by the ERC under the EU's H2020 Programme Grant 725594, Hasler Foundation under Project 16066, Bertarelli foundation and SNSF Grant CRSII5_183519.
Funders:
Funding AgencyGrant Number
European Research Council (ERC)725594
Hasler Foundation16066
Bertarelli FoundationUNSPECIFIED
Swiss National Science Foundation (SNSF)CRSII5_183519
Record Number:CaltechAUTHORS:20210528-094923310
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210528-094923310
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109295
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:28 May 2021 22:43
Last Modified:28 May 2021 22:43

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