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Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG

Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG

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 Automatic Seizure Detection Using Wavelet Transform and SVM in Long-Term Intracranial EEG

Automatic seizure detection is of great signi fi cance for epilepsy long-term monitoring, diagno sis, and rehabilita-tion, and it is the key to closed-loop brain stimulation. This paper presents a novel wavelet-based automatic seizure detection method with high sensitivity. The proposed method fi rst conducts wavelet decomposition of multi-channel intracranial EEG (iEEG) with fi ve scales, and selects three frequency bands of them for subsequent processing. Effective features are extracted, such as relative energy, relative amplitude, coef fi cient of variation and fl uctuation index at the selected scales, and then these features are sent into the support vecto r machine for training and clas-si fi cation. Afterwards a postproces sing is applied on the rawclassifi cation results to obtain more accurate and stable results. Postprocessing include s smoothing, multi-channel decision fusion and collar technique. Its performance is evaluated on a large dataset of 509 h from 21 epileptic patients. Experiments show that the proposed method co uld achieve a sensitivity of 94.46% and aspecifi city of 95.26% with a false detection rate of 0.58/h for seizure detection in long-term iEEG.


 


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  • Model: PROJ7686
  • 999 Units in Stock
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This product was added to our catalog on Wednesday 09 August, 2017.

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