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An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy

Zamani, M; Jiang, D; Demosthenous, A; (2018) An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy. IEEE Transactions on Biomedical Circuits and Systems , 12 (3) pp. 665-676. 10.1109/TBCAS.2018.2825421. Green open access

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Abstract

There is a need for integrated spike sorting processors in implantable devices with low power consumption that have improved accuracy. Learning the characteristics of the variable input neural signals and adapting the functionality of the sorting process can improve the accuracy. An adaptive spike sorting processor is presented accounting for the variation in the input signal noise characteristics and the variable difficulty in the selection of the spike characteristics, which significantly improves the accuracy. The adaptive spike processor was fabricated in 180-nm CMOS technology for proof of concept. It performs conditional detection, alignment, adaptive feature extraction, and online clustering with sorting threshold self-tuning capability. The chip was tested under different input signal conditions to demonstrate its adaptation capability providing a median classification accuracy of 84.5 & #x0025; and consuming 148 & #x03BC;W from a 1.8 V supply voltage.

Type: Article
Title: An Adaptive Neural Spike Processor With Embedded Active Learning for Improved Unsupervised Sorting Accuracy
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TBCAS.2018.2825421
Publisher version: http://dx.doi.org/10.1109/TBCAS.2018.2825421
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Adaptive decomposition, brain machine interface, feature extraction, processor, reconfigurable embedded frames, signal model learning, spike sorting, unsupervised clustering.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10049967
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