Related papers: Spike-and-wave epileptiform discharge pattern dete…
We report a high-statistics measurement of the branching fraction for tau^- --> pi^- pi^0 nu_tau and the invariant mass spectrum of the produced pi^- pi^0 system using 72.2 fb^-1 of data recorded with the Belle detector at the KEKB…
In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the…
Analyzing electroencephalogram (EEG) signals to detect the epileptic seizure status of a subject presents a challenge to existing technologies aimed at providing timely and efficient diagnosis. In this study, we aimed to detect interictal…
Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide,…
A preliminary measurement of the branching fraction B(tau- --> K0 pi- nu) is made using 384.6 fb-1 of e+e- collision data provided by the PEP-II collider, operating primarily at sqrt(s)=10.58 GeV, and recorded using the BaBar detector. From…
This contribution reports an application of MultiFractal Detrended Fluctuation Analysis, MFDFA based novel feature extraction technique for automated detection of epilepsy. In fractal geometry, Multifractal Detrended Fluctuation Analysis…
For the past few years, we have developed flexible, active, multiplexed recording devices for high resolution recording over large, clinically relevant areas in the brain. While this technology has enabled a much higher-resolution view of…
Epilepsy is one of the most common neurological diseases, characterized by transient and unprovoked events called epileptic seizures. Electroencephalogram (EEG) is an auxiliary method used to perform both the diagnosis and the monitoring of…
A new and simple method of blood bilirubin detection through light reflection from skin is developed. The basic improvement over the existing methods is in the design of the light emitter and detector geometry which facilitates a two-stream…
Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and…
In clinical practice, electroencephalography (EEG) plays an important role in the diagnosis of epilepsy. EEG-based computer-aided diagnosis of epilepsy can greatly improve the ac-curacy of epilepsy detection while reducing the workload of…
Burst-suppression (BS) is a reliable electroencephalogram (EEG) indicator of excessive deep anesthesia common in mammals. Since some intermittent events are known to follow a power-law, we investigated the power-law hypothesis in BS by…
A measurement of the tau- --> K- pi0 nu_tau branching fraction has been made using 230.2 fb-1 of data recorded by the BABAR detector at the PEP-II e+ e- collider, located at the Stanford Linear Accelerator Center (SLAC), at a center of mass…
Stroke poses an immense public health burden and remains among the primary causes of death and disability worldwide. Emergent therapy is often precluded by late or indeterminate times of onset before initial clinical presentation. Rapid,…
We propose a computationally efficient algorithm for seizure detection. Instead of using a purely data-driven approach, we develop a hybrid model-based/data-driven method, combining convolutional neural networks with factor graph inference.…
Introduction: The HAS conducted a study in 2018 using the French National Health Data System (SNDS) on the care pathway of patients with epilepsy. This study used 2 algorithms to identify patients with epilepsy, based on hospitalization for…
It has been demonstrated that acoustic-emission (AE), inspection of structures can offer advantages over other types of monitoring techniques in the detection of damage; namely, an increased sensitivity to damage, as well as an ability to…
In this paper, a genetic algorithm-based frequency-domain feature search (GAFDS) method is proposed for the electroencephalogram (EEG) analysis of epilepsy. In this method, frequency-domain features are first searched and then combined with…
A Magnetoencephalography (MEG) time-series recording consists of multi-channel signals collected by superconducting sensors, with each signal's intensity reflecting magnetic field changes over time at the sensor location. Automating…
Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences…