Early Seizure Detection by Applying Frequency-Based Algorithm Derived from the Principal Component Analysis.

ABSTRACT: The use of automatic electrical stimulation in response to early seizure detection has been introduced as a new treatment for intractable epilepsy. For the effective application of this method as a successful treatment, improving the accuracy of the early seizure detection is crucial. In this paper, we proposed the application of a frequency-based algorithm derived from principal component analysis (PCA), and demonstrated improved efficacy for early seizure detection in a pilocarpine-induced epilepsy rat model. A total of 100 ictal electroencephalographs (EEG) during spontaneous recurrent seizures from 11 epileptic rats were finally included for the analysis. PCA was applied to the covariance matrix of a conventional EEG frequency band signal. Two PCA results were compared: one from the in

SUBMITTER: Lee J 

PROVIDER: S-EPMC5562675 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature