Scalable and energy efficient seizure detection based on direct use of compressively-sensed EEG data on an ultra low power multi-core architecture.

Extracting information from dense multi-channel neural sensors for accurate diagnosis of brain disorders necessitates computationally expensive and advanced signal processing approaches to analyze the massive volume of recorded data. Compressive Sensing (CS) is an efficient method for reducing the computational complexity and power consumption in the resource-constrained multi-site neural systems. However, reconstructing the signal from compressed measurements is computationally intensive, making it unsuitable for real-time applications such as seizure detection.

Simulation of effects of the electrode structure and material in the density measuring system of the peripheral nerve based on micro-electrical impedance tomography.

The electrode structure in micro-electrical impedance tomography (MEIT) highly influences the measurement sensitivity and therefore the reconstructed image quality. Hence, optimizing the electrode structure leads to the improvement of image quality in the reconstruction procedure. Although there have been many investigations on electrical impedance tomography (EIT) electrodes, there is no comprehensive study on their influence on images of the peripheral nerve.

Assessment on selectivity of multi-contact cuff electrode for recording peripheral nerve signals using Fitzhugh-Nagumo model of nerve excitation.

Background: Nerve cuff electrodes provide a safe technique for recording nerve signals. Defining a more realized modeling to investigate the selectivity of a cuff electrode in recording from peripheral nervous system is an interesting field of research.

Methods: A four-contact cuff electrode was modeled to evaluate selective recording from a peripheral nerve.

Effect of contacts configuration and location on selective stimulation of cuff electrode.

Background: Cuff electrodes have been widely used chronically in different clinical applications. Advancements have been made in selective stimulation by using multi-contact cuff electrodes. Steering anodic current is a strategy to increase selectivity by reshaping and localizing electric fields.

An autonomous real-time single-channel detection of absence seizures in WAG/Rij rats.

This paper presents a real-time, completely automated and patient independent algorithm for detection of absence seizures in WAG/Rij rats as a valid animal model of human absence epilepsy. Single-channel EEG recordings containing totally 488 seizures from 8 WAG/Rij rats were analyzed using the real-time SWD detection algorithm. The proposed algorithms based on the variation of wavelet power to the background power in two specific frequency bands whose spectral power are highly correlated with SWDs.

Investigation of ECG Changes in Absence Epilepsy on WAG/Rij Rats.

Introduction: Seizures are symptoms associated with abnormal electrical activity in electroencephalogram (EEG). The present study was designed to determine the effect of absence seizure on heart rate (HR) changes in electrocardiogram (ECG).

Methods: HR alterations were recorded simultaneous with spike and wave discharges (SWD) by EEG in 6 WAG/Rij rats as a well characterized and validated genetic animal epilepsy model.