Add to ORKGAbstract: In this paper we consider the stationary level of electroencephalogram time series. It appears, that local increase of this indicator can be chosen as a predictor of an attack of epilepsy. The recognition of this attack has a statistical error of the first kind 40 % and the second kind 10 %.Note: Research direction:Mathematical modelling in actual problems of science and technic
The relation between the presence of latent epileptiform process and the change of the instantaneous...
A number of stochastic models and statistical tests are synthesised to develop a general framework f...
The present study introduces the method for solving the problem on early prediction of epilepsy seiz...
Abstract: In this paper we consider the self-consistent stationary level of electroencepha...
The quantitative analysis of the electroencephalogram (EEG) relies heavily on methods of time series...
The correlation dimension has been used to characterize the effect of anesthesia on the EEG [13][14]...
Symptoms of epilepsy, which is characterized by abnormal brain electrical activity, can be observed ...
In the study of epileptic seizure or epileptic attack , a strategy receiving increased attention is ...
This paper presents results of a non-linear study of the human electroencephalogram to establish the...
Human epilepsy is a disease characterized by sudden, unprovoked, recurrent seizures accompanied by p...
Since its first description, quantifying the burden of epileptiform abnormalities in sleep EEG has p...
Symptoms of epilepsy, which is characterized by abnor-mal brain electrical activity, can be observed...
The problem of seizure anticipation in patients with epilepsy has attracted significant attention in...
Recurrence plots are widely used in the analysis of complex dynamic systems. A good example of compl...
Abstract: Self-consistent stationary level of non-stationary time series is investigated. ...
The relation between the presence of latent epileptiform process and the change of the instantaneous...
A number of stochastic models and statistical tests are synthesised to develop a general framework f...
The present study introduces the method for solving the problem on early prediction of epilepsy seiz...
Abstract: In this paper we consider the self-consistent stationary level of electroencepha...
The quantitative analysis of the electroencephalogram (EEG) relies heavily on methods of time series...
The correlation dimension has been used to characterize the effect of anesthesia on the EEG [13][14]...
Symptoms of epilepsy, which is characterized by abnormal brain electrical activity, can be observed ...
In the study of epileptic seizure or epileptic attack , a strategy receiving increased attention is ...
This paper presents results of a non-linear study of the human electroencephalogram to establish the...
Human epilepsy is a disease characterized by sudden, unprovoked, recurrent seizures accompanied by p...
Since its first description, quantifying the burden of epileptiform abnormalities in sleep EEG has p...
Symptoms of epilepsy, which is characterized by abnor-mal brain electrical activity, can be observed...
The problem of seizure anticipation in patients with epilepsy has attracted significant attention in...
Recurrence plots are widely used in the analysis of complex dynamic systems. A good example of compl...
Abstract: Self-consistent stationary level of non-stationary time series is investigated. ...
The relation between the presence of latent epileptiform process and the change of the instantaneous...
A number of stochastic models and statistical tests are synthesised to develop a general framework f...
The present study introduces the method for solving the problem on early prediction of epilepsy seiz...