Tenneti, Srikanth V. and Vaidyanathan, P. P. (2018) Absence Seizure Detection Using Ramanujan Filter Banks. In: 52nd Asilomar Conference on Signals, Systems, and Computers. IEEE , Piscataway, NJ, pp. 1913-1917. ISBN 978-1-5386-9218-9. https://resolver.caltech.edu/CaltechAUTHORS:20190301-152543153
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Abstract
Absence seizures are a type of generalized seizures characterized by a 3 Hz periodic spike and wave discharge pattern in the Electroencephalogram (EEG). The most common way to diagnose them is by detecting such periodic patterns in a patient’s EEG. Recently, a new method known as Ramanujan Filter Bank (RFB) was proposed for identifying, estimating and localizing periodicities in data. The RFB was shown to offer important advantages over traditional period estimation techniques in DSP. In this work, we demonstrate that the RFB offers very useful diagnostic information when applied to EEG signals from absence-seizure patients.
| Item Type: | Book Section | ||||||||||
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| Additional Information: | © 2018 IEEE. This work was supported in parts by the ONR grants N00014-17-1-2732 and N00014-18-1-2390, the NSF grant CCF-1712633, and an Amazon post doctoral fellowship facilitated through the Information Science and Technology (IST) initiative at Caltech. | ||||||||||
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| DOI: | 10.1109/ACSSC.2018.8645492 | ||||||||||
| Record Number: | CaltechAUTHORS:20190301-152543153 | ||||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190301-152543153 | ||||||||||
| Official Citation: | S. V. Tenneti and P. P. Vaidyanathan, "Absence Seizure Detection Using Ramanujan Filter Banks," 2018 52nd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2018, pp. 1913-1917. doi: 10.1109/ACSSC.2018.8645492 | ||||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||
| ID Code: | 93403 | ||||||||||
| Collection: | CaltechAUTHORS | ||||||||||
| Deposited By: | Tony Diaz | ||||||||||
| Deposited On: | 01 Mar 2019 23:35 | ||||||||||
| Last Modified: | 16 Nov 2021 16:57 |
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