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This paper presents a novel wearable biomedical Network on Chip (NoC) concept development to monitor and predict irregular brain waves as advanced sensitive portable for an electroencephalogram (EEG) analysis device. The proposed device will monitor brain’s spontaneous electrical activity in normal and abnormal situations for specific patients suffering from different types of epilepsy...
Real signals are often corrupted by noise. In applications where the noise power spectrum is variable with time, dynamic noise estimation and compensation can potentially improve the performance of signal processing algorithms. One such application is scalp EEG monitoring in epilepsy, where the electrical activity generated by cranio-facial muscle contraction and expansion, often obscures the measured...
This paper presents a novel theoretical paradigm for epileptic seizure prediction based on a coupled oscillator model of brain dynamics. This model is used to investigate prediction methods capable of tracking the synchronization changes that may lead to a seizure. Previous results indicate that state-space reconstruction of a coupled oscillator model from an EEG-like signal is ill-posed, therefore,...
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