Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning

Personalizing Heart Rate-Based Seizure Detection Using Supervised SVM Transfer Learning

Objective: Automated seizure detection is a key aspect of wearable seizure warning systems. As a result, the quality of life of refractory epilepsy patients could be improved. Most state-of-the-art algorithms for heart rate-based seizure detection use a so-called patient-independent approach, which...

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Bibliographic Details
Main Authors: Thomas De Cooman, Kaat Vandecasteele, Carolina Varon, Borbála Hunyadi, Evy Cleeren, Wim Van Paesschen, Sabine Van Huffel
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-02-01
Series:Frontiers in Neurology
Subjects:
epilepsy
transfer learning
seizure detection
personalization
heart rate analysis
SVM
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2020.00145/full

Internet

https://www.frontiersin.org/article/10.3389/fneur.2020.00145/full

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