Machine Learning Analysis of Heart Rate Variability for the Detection of Seizures in Comatose Cardiac Arrest Survivors

Machine Learning Analysis of Heart Rate Variability for the Detection of Seizures in Comatose Cardiac Arrest Survivors

Objective: Heart rate variability (HRV) reflects autonomous nervous system disturbance and is used for seizure prediction. The aim of this study was to develop a real-time, continuous physiological medical signal data acquisition system in seizure detection for intensive care unit (ICU). Methods: Th...

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Bibliographic Details
Main Authors: Chih-Wei Sung, Jiann-Shing Shieh, Wei-Tien Chang, Yi-Wei Lee, Ji-Huan Lyu, Hooi-Nee Ong, Wei-Ting Chen, Chien-Hua Huang, Wen-Jone Chen, Fu-Shan Jaw
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Heart rate variability
seizure
cardiac arrest
machine learning
electroencephalography
Online Access:https://ieeexplore.ieee.org/document/9181556/

Internet

https://ieeexplore.ieee.org/document/9181556/

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