Main Reference PaperAn Adaptive Pattern Learning Framework to Personalize Online Seizure Prediction, IEEE Transactions on Big Data, March 2017 [R].
  • The approaches such as the adaptive probabilistic prediction (APP), adaptive lineardiscriminant- analysis-based prediction (ALP), and adaptive Naive Bayes-based prediction (ANBP) are proposed in which pre-seizure and normal patterns are extracted from massive multivariate EEG data of the patient.

Description
  • The approaches such as the adaptive probabilistic prediction (APP), adaptive lineardiscriminant- analysis-based prediction (ALP), and adaptive Naive Bayes-based prediction (ANBP) are proposed in which pre-seizure and normal patterns are extracted from massive multivariate EEG data of the patient.

  • To classify pre-seizure and normal patterns.

  • To generate the pattern library of patient individually .

Aim & Objectives
  • To classify pre-seizure and normal patterns.

  • To generate the pattern library of patient individually .

  • Adaptive prediction system is improved further to achieve accurate personalized seizure prediction.

Contribution
  • Adaptive prediction system is improved further to achieve accurate personalized seizure prediction.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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