Dec 24, 2015 · The present study proposes a new epileptic seizure prediction method through integrating heart rate variability (HRV) analysis and an anomaly monitoring ...
Epileptic Seizure Prediction Based on Multivariate Statistical Process ...
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The proposed method consists of two parts: HRV feature extraction from RRI data of epileptic patients, and epileptic seizure prediction by utilizing an anomaly ...
May 12, 2024 · In the proposed method, eight HRV features are monitored for predicting seizures by using multivariate statistical process control (MSPC), which ...
May 25, 2016 · We proposed a new epileptic seizure prediction algorithm based on HRV. The proposed algorithm is as follows: 1) extract eight typical HRV features from RRI ...
The application results of the proposed method demonstrated that seizures in ten out of eleven awakening preictal episodes could be predicted prior to the ...
The present work proposes an HRV-based epileptic seizure monitoring method by utilizing multivariate statistical process control (MSPC) technology.
Jan 27, 2024 · A higher accuracy is achieved by using multivariate approaches, where different HRV features, also of different domains, are aggregated ...
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In this paper, we proposed a new method to predict epileptic seizures using heart rate variability (HRV) signal analysis. During preictal period of epilepsy, ...
Apr 1, 2016 · In the proposed method, eight HRV features are monitored for predicting seizures by using multivariate statistical process control (MSPC), which ...
Sep 25, 2018 · The aim of this study was to develop a patient-specific approach to predict seizures using electrocardiogram (ECG) features.