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A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection

Taghavi, Milad and Haghi, Benyamin A. and Farivar, Masoud and Shoaran, Mahsa and Emami, Azita (2018) A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection. In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE , Piscataway, NJ, pp. 3693-3696. ISBN 978-1-5386-3646-6. http://resolver.caltech.edu/CaltechAUTHORS:20181102-143405625

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Abstract

A 41.2 nJ/class, 32-channel, patient-specific onchip classification architecture for epileptic seizure detection is presented. The proposed system-on-chip (SoC) breaks the strict energy-area-delay trade-off by employing area and memoryefficient techniques. An ensemble of eight gradient-boosted decision trees, each with a fully programmable Feature Extraction Engine (FEE) and FIR filters are continuously processing the input channels. In a closed-loop architecture, the FEE reuses a single filter structure to execute the top-down flow of the decision tree. FIR filter coefficients are multiplexed from a shared memory. The 540 × 1850 μm 2 prototype with a 1kB register-type memory is fabricated in a TSMC 65nm CMOS process. The proposed on-chip classifier is verified on 2253 hours of intracranial EEG (iEEG) data from 20 patients including 361 seizures, and achieves specificity of 88.1% and sensitivity of 83.7%. Compared to the state-of-the-art, the proposed classifier achieves 27 × improvement in Energy-AreaLatency product.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/EMBC.2018.8513243DOIArticle
https://ieeexplore.ieee.org/document/8513243PublisherArticle
ORCID:
AuthorORCID
Emami, Azita0000-0003-2608-9691
Additional Information:© 2018 IEEE.
Record Number:CaltechAUTHORS:20181102-143405625
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20181102-143405625
Official Citation:M. Taghavi, B. A. Haghi, M. Farivar, M. Shoaran and A. Emami, "A 41.2 nJ/class, 32-Channel On-Chip Classifier for Epileptic Seizure Detection," 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA, 2018, pp. 3693-3696. doi: 10.1109/EMBC.2018.8513243
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:90620
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:02 Nov 2018 22:06
Last Modified:30 Jan 2019 00:00

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