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Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

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 Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

 Objective: The present study proposes a new epileptic seizure prediction method through integrating heart rate variability (HRV) analysis and an anomaly monitoring technique. Methods: Because excessive neuronal activities in the preictal period of epilepsy affect the autonomic nervous systems and autonomic nervous function affects HRV, it is assumed that a seizure can be predicted through monitoring HRV. In the proposed method, eight HRV features are monitored for predicting seizures by using multivariate statistical process control, which is a well-known anomaly monitoring method.


 


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  • Model: PROJ7222
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Saturday 17 June, 2017.

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