Novel Method to Classify Epileptic and Non-Epileptic Seizures Using Wearable Watch Data (P5-9.007)

To demonstrate the feasibility of using wearable data to distinguish between epileptic and non-epileptic seizures using a modified Convolutional Neural Network (CNN) model.

Authors

Jennifer Zhou (ORCID: https://orcid.org/0000-0001-8489-5718)
Akane Sano (ORCID: https://orcid.org/0000-0003-4484-8946)
Zulfi Haneef (ORCID: https://orcid.org/0000-0002-0720-1417)
Sruthi Gopinath Karicheri
Peikun Guo

Institutions

Baylor College of Medicine (US)
Rice University (US)

Publication Details

Journal: Neurology
Published: 2025-04-07
DOI: https://doi.org/10.1212/wnl.0000000000212654
Primary Topic: EEG and Brain-Computer Interfaces
Type: article
Field-Weighted Citation Impact: 0.00

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article

Novel Method to Classify Epileptic and Non-Epileptic Seizures Using Wearable Watch Data (P5-9.007)

Jennifer Zhou, Akane Sano, Zulfi Haneef, Sruthi Gopinath Karicheri et al.

Apr 7, 2025

Neurology

EEG and Brain-Computer Interfaces

article

Novel Method to Classify Epileptic and Non-Epileptic Seizures Using Wearable Watch Data (P5-9.007)

Jennifer Zhou, Akane Sano, Zulfi Haneef, Sruthi Gopinath Karicheri, Peikun Guo

April 7, 2025article en

Abstract

To demonstrate the feasibility of using wearable data to distinguish between epileptic and non-epileptic seizures using a modified Convolutional Neural Network (CNN) model.

NeurologyVol. 104(7_Supplement_1)

Baylor College of Medicine (US), Rice University (US)

Gender equality

Openalex Percentile: Top 94%

EEG and Brain-Computer Interfaces

DOI Source OpenAlex

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