Shoaran, Mahsa and Farivar, Masoud and Emami-Neyestanak, Azita (2016) Hardware-friendly seizure detection with a boosted ensemble of shallow decision trees. In: 2016 IEEE 38th Annual International Conference of the Engineering in Medicine and Biology Society (EMBC). IEEE , Piscataway, NJ, pp. 1826-1829. ISBN 978-1-4577-0220-4. https://resolver.caltech.edu/CaltechAUTHORS:20161020-133924609
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Abstract
Efficient on-chip learning is becoming an essential element of implantable biomedical devices. Despite a substantial literature on automated seizure detection algorithms, hardware-friendly implementation of such techniques is not sufficiently addressed. In this paper, we propose to employ a gradientboosted ensemble of decision trees to achieve a reasonable trade-off between detection accuracy and implementation cost. Combined with the proposed feature extraction model, we show that these classifiers quickly become competitive with more complex learning models previously proposed for hardware implementation, with only a small number of low-depth (d < 4) “shallow” trees. The results are verified on more than 3460 hours of intracranial EEG data including 430 seizures from 27 patients with epilepsy.
Item Type: | Book Section | |||||||||
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Additional Information: | © 2016 IEEE. | |||||||||
DOI: | 10.1109/EMBC.2016.7591074 | |||||||||
Record Number: | CaltechAUTHORS:20161020-133924609 | |||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20161020-133924609 | |||||||||
Official Citation: | M. Shoaran, M. Farivar and A. Emami, "Hardware-friendly seizure detection with a boosted ensemble of shallow decision trees," 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2016, pp. 1826-1829. doi: 10.1109/EMBC.2016.7591074 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7591074&isnumber=7590615 | |||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
ID Code: | 71322 | |||||||||
Collection: | CaltechAUTHORS | |||||||||
Deposited By: | Tony Diaz | |||||||||
Deposited On: | 20 Oct 2016 21:47 | |||||||||
Last Modified: | 11 Nov 2021 04:43 |
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